Rationally Integrating Charge-Transfer Cocrystal and Ni(II) Organometallics for Visualized Photo/Thermochromic Sensors.

Smart materials demonstrate fascinating responses to environmental physical/chemical stimuli, including thermal, photonic, electronic, humidity, or magnetic stimuli, which have attracted intensive interest in material chemistry. However, their limited/harsh stimuli-responsive behavior or sophisticated postprocessing leads to enormous challenges for practical applications. Herein, we rationally designed and synthesized thermochromic Ni(II) organometallic [(C2H5)2NH2]2NiCl4-xBrx via a facile mechanochemical strategy, which demonstrated a reversible switch from yellow to blue color with a tunable phase-transition temperature from 75.6 to 61.7 °C. The simple electrospinning technology was applied to fabricate thermochromic Ni(II) organometallic-based nanofiber membranes for temperature monitoring. Furthermore, the organic charge-transfer cocrystal with a wide spectral absorption of 300-1950 nm and a high-efficiency photothermal conversion was combined with thermochromic Ni(II) organometallics for the desired dual-stimuli photo/thermochromism. This work supplies a new strategy for realizing multiple stimuli-responsive applications, such as thermal/light sensor displays and information storage.

A novel surgical scheme for hepatectomy in hepatocellular carcinoma patients with clinically significant portal hypertension.

OBJECTIVE: Clinically significant portal hypertension (CSPH) seriously affects the feasibility and safety of surgical treatment for hepatocellular carcinoma (HCC) patients. The aim of this study was to establish a new surgical scheme defining risk classification of post-hepatectomy liver failure (PHLF) to facilitate the surgical decision-making and identify suitable candidates for individual hepatectomy among HCC patients with CSPH. BACKGROUNDS: Hepatectomy is the preferred treatment for HCC. Surgeons must maintain a balance between the expected oncological outcomes of HCC removal and short-term risks of severe PHLF and morbidity. CSPH aggravates liver decompensation and increases the risk of severe PHLF thus complicating hepatectomy for HCC. METHODS: Multivariate logistic regression and stochastic forest algorithm were performed, then the independent risk factors of severe PHLF were included in a nomogram to determine the risk of severe PHLF. Further, a conditional inference tree (CTREE) through recursive partitioning analysis validated supplement the misdiagnostic threshold of the nomogram. RESULTS: This study included 924 patients, of whom 137 patients (14.8%) suffered from mild-CSPH and 66 patients suffered from (7.1%) with severe-CSPH confirmed preoperatively. Our data showed that preoperative prolonged prothrombin time, total bilirubin, indocyanine green retention rate at 15 min, CSPH grade, and standard future liver remnant volume were independent predictors of severe PHLF. By incorporating these factors, the nomogram achieved good prediction performance in assessing severe PHLF risk, and its concordance statistic was 0.891, 0.850 and 0.872 in the training cohort, internal validation cohort and external validation cohort, respectively, and good calibration curves were obtained. Moreover, the calculations of total points of diagnostic errors with 95% CI were concentrated in 110.5 (range 76.9-178.5). It showed a low risk of severe PHLF (2.3%), indicating hepatectomy is feasible when the points fall below 76.9, while the risk of severe PHLF is extremely high (93.8%) and hepatectomy should be rigorously restricted at scores over 178.5. Patients with points within the misdiagnosis threshold were further examined using CTREE according to a hierarchic order of factors represented by the presence of CSPH grade, ICG-R15, and sFLR. CONCLUSION: This new surgical scheme established in our study is practical to stratify risk classification in assessing severe PHLF, thereby facilitating surgical decision-making and identifying suitable candidates for individual hepatectomy.

Assessment of causal relationships between omega-3 and omega-6 polyunsaturated fatty acids in autoimmune rheumatic diseases: a brief research report from a Mendelian randomization study.

Background: Currently, the association between the consumption of polyunsaturated fatty acids (PUFAs) and the susceptibility to autoimmune rheumatic diseases (ARDs) remains conflict and lacks substantial evidence in various clinical studies. To address this issue, we employed Mendelian randomization (MR) to establish causal links between six types of PUFAs and their connection to the risk of ARDs. Methods: We retrieved summary-level data on six types of PUFAs, and five different types of ARDs from publicly accessible GWAS statistics. Causal relationships were determined using a two-sample MR analysis, with the IVW approach serving as the primary analysis method. To ensure the reliability of our research findings, we used four complementary approaches and conducted multivariable MR analysis (MVMR). Additionally, we investigated reverse causality through a reverse MR analysis. Results: Our results indicate that a heightened genetic predisposition for elevated levels of EPA (ORIVW: 0.924, 95% CI: 0.666-1.283, P IVW = 0.025) was linked to a decreased susceptibility to psoriatic arthritis (PsA). Importantly, the genetically predicted higher levels of EPA remain significantly associated with an reduced risk of PsA, even after adjusting for multiple testing using the FDR method (P IVW-FDR-corrected = 0.033) and multivariable MR analysis (P MV-IVW < 0.05), indicating that EPA may be considered as the risk-protecting PUFAs for PsA. Additionally, high levels of LA showed a positive causal relationship with a higher risk of PsA (ORIVW: 1.248, 95% CI: 1.013-1.538, P IVW = 0.037). It is interesting to note, however, that the effects of these associations were weakened in our MVMR analyses, which incorporated adjustment for lipid profiles (P MV-IVW > 0.05) and multiple testing using the FDR method (P IVW-FDR-corrected = 0.062). Moreover, effects of total omega-3 PUFAs, DHA, EPA, and LA on PsA, were massively driven by SNP effects in the FADS gene region. Furthermore, no causal association was identified between the concentrations of other circulating PUFAs and the risk of other ARDs. Further analysis revealed no significant horizontal pleiotropy and heterogeneity or reverse causality. Conclusion: Our comprehensive MR analysis indicated that EPA is a key omega-3 PUFA that may protect against PsA but not other ARDs. The FADS2 gene appears to play a central role in mediating the effects of omega-3 PUFAs on PsA risk. These findings suggest that EPA supplementation may be a promising strategy for preventing PsA onset. Further well-powered epidemiological studies and clinical trials are warranted to explore the potential mechanisms underlying the protective effects of EPA in PsA.

Ginsenoside Rg1 promotes neurite growth of retinal ganglion cells through cAMP/PKA/CREB pathways.

Background: Mechanisms of synaptic plasticity in retinal ganglion cells (RGCs) are complex and the current knowledge cannot explain. Growth and regeneration of dendrites together with synaptic formation are the most important parameters for evaluating the cellular protective effects of various molecules. The effect of ginsenoside Rg1 (Rg1) on the growth of retinal ganglion cell processes has been poorly understood. Therefore, we investigated the effect of ginsenoside Rg1 on the neurite growth of RGCs. Methods: Expression of proteins and mRNA were detected by Western blot and qPCR. cAMP levels were determined by ELISA. In vivo effects of Rg1 on RGCs were evaluated by hematoxylin and eosin, and immunohistochemistry staining. Results: This study found that Rg1 promoted the growth and synaptic plasticity of RGCs neurite by activating the cAMP/PKA/CREB pathways. Meanwhile, Rg1 upregulated the expression of GAP43, Rac1 and PAX6, which are closely related to the growth of neurons. Meantime, H89, an antagonist of PKA, could block this effect of Rg1. In addition, we preliminarily explored the effect of Rg1 on enhancing the glycolysis of RGCs, which could be one of the mechanisms for its neuroprotective effects. Conclusion: Rg1 promoted neurite growth of RGCs through cAMP/PKA/CREB pathways. This study may lay a foundation for its clinical use of optic nerve diseases in the future.

C-Reactive Protein-Albumin Ratio (CAR): A More Promising Inflammation-Based Prognostic Marker for Patients Undergoing Curative Hepatectomy for Hepatocellular Carcinoma.

Background: Systemic inflammatory response is a hallmark of cancer and plays a significant role in the development and progression of various malignant tumors. This research aimed to estimate the prognostic function of the C-reactive protein-albumin ratio (CAR) in patients undergoing hepatectomy for hepatocellular carcinoma (HCC) and compare it with other inflammation-based prognostic scores, including the neutrophil-lymphocyte ratio, platelet-lymphocyte ratio, monocyte-lymphocyte ratio, systemic immune inflammation index, prognostic index, Glasgow prognostic score, and modified Glasgow prognostic score. Methods: Retrospective analysis was conducted on data from 1039 HCC cases who underwent curative liver resection. The prognostic performance of CAR was compared with other scores using the area under the time-dependent receiver operating characteristic (t-ROC) curve. Multivariable Cox regression analyses were performed to confirm independent predictors for disease-free survival (DFS) and overall survival (OS). Results: The area under the t-ROC curve for CAR in the evaluation of DFS and OS was significantly greater than that of other scores and alpha-fetoprotein (AFP). Patients were stratified based on the optimal cut-off value of CAR, and the data revealed that both DFS and OS were remarkably worse in the high-CAR set compared to the low-CAR set. Multivariable Cox analysis demonstrated that CAR was an independent prognostic parameters for assessing DFS and OS. Regardless of AFP levels, all patients were subsequently divided into significantly different subgroups of DFS and OS based on CAR risk stratification. Similar results were observed when applying CAR risk stratification to other scoring systems. CAR also showed good clinical applicability in patients with different clinical features. Conclusion: CAR is a more effective inflammation-based prognostic marker than other scores and AFP in predicting DFS as well as OS among patients with HCC after curative hepatectomy.

Potential Targets and Mechanisms of Jiedu Quyu Ziyin Decoction for Treating SLE-GIOP: Based on Network Pharmacology and Molecular Docking.

Background: Systemic lupus erythematosus (SLE) is characterized by poor regulation of the immune response leading to chronic inflammation and multiple organ dysfunction. Glucocorticoid (GC) is currently one of the main treatments. However, a high dose or prolonged use of GC may result in glucocorticoid-induced osteoporosis (GIOP). Jiedu Quyu Ziyin decoction (JP) is effective in treating SLE and previous clinical studies have proved that JP can prevent and treat SLE steroid osteoporosis (SLE-GIOP). We aim to examine JPs main mechanism on SLE-GIOP through network pharmacology and molecular docking. Methods: TCMSP and TCMID databases were used to screen potential active compounds and targets of JP. The SLE-GIOP targets are collected from GeneCards, OMIM, PharmGkb, TTD, and DrugBank databases. R software was used to obtain the cross-targets of JP and SLE-GIOP and to perform GO and KEGG enrichment analysis. Cytoscape software was used to make the Chinese Medicines-Active Ingredient-Intersection Targets network diagram. STRING database construct protein-protein interaction network and obtain the core targets. Auto Dock Tools and Pymol software were used for docking. Results: Fifty eight targets overlapped between JP and SLE-GIOP were suggested as potential targets of JP in the treatment of SLE-GIOP. Network topology analysis identified five core targets. GO enrichment analysis was obtained 1,968 items, and the top 10 biological process, closeness centrality, and molecular function were displayed. A total of 154 signaling pathways were obtained by KEGG enrichment analysis, and the top 30 signaling pathways were displayed. JP was well bound by MAPK1, TP53, and MYC according to the molecular docking results. Conclusion: We investigated the potential targets and signaling pathways of JP against SLE-GIOP in this study. It shows that JP is most likely to achieve the purpose of treating SLE-GIOP by promoting the proliferation and differentiation of osteoblasts. A solid theoretical foundation will be provided for the future study of clinical and experimental topics.

The expression levels of NF-κB and IKKß in epithelial ovarian cancer and their correlation with drug resistance-related genes MDR1, TOPOII, and ERCC1.

OBJECTIVES: To explore the expression levels of nuclear factor kappa B (NF-κB) and inhibitor of nuclear factor kappa B kinase (IKKß) in epithelial ovarian cancer and the correlation analysis with multi-drug resistance-related genes 1 (MDR1), topoisomerase II (TOPOII) and nucleotide excision repair cross complementary group 1 (ERCC1). METHODS: Immunohistochemical methods were used to detect the expression levels of NF-κB and IKKß in epithelial ovarian cancer group (50 cases), ovarian benign tumor group (30 cases), and normal ovary group (10 cases). The expression levels of NF-κB, IKKß, MDR1, TOPOII and ERCC1 messenger ribonucleic acid (mRNA) and protein were analyzed using real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot. Student's t-test and one-way ANOVA were used for comparison of numerical data. Pearson's chi-squared and Fisher's exact tests were carried out for analysis of non-numerical data. RESULTS: The levels of NF-κB, IKKß, MDR1 and ERCC1 mRNA and protein were increased (P<0.05), and the expression levels of TOPOII were decreased (P<0.05) in the epithelial ovarian cancer group compared to the normal ovary and benign ovarian tumor groups. The expression of NF-κB and IKKß in epithelial ovarian cancer was significantly increased in patients with higher tumor stage, lower differentiation and presence of lymph node metastasis and positively correlated with MDR1 expression. NF-κB and IKKß were negatively correlated with the expression of TOPOII and antagonized each other with TOPOII. CONCLUSIONS: The expression of NF-κB and IKKß was positively correlated with the expression of MDR1, and negatively correlated with the expression of TOPOII. The correlation of NF-κB, IKKß and resistance related genes, including MDR1, TOPOII, ERCC1, can predict the resistance of chemotherapy individuals to chemotherapy.

Simultaneous determination of Panax notoginseng total saponins in rabbit tears by UPLC-QqQ-MS/MS and its application to pharmacokinetic study.

Panax notoginseng total saponins (PNS), the main bioactive components of the radix and rhizome of Panax notoginseng (Burk.) F.H. Chen, could treat eye disorders. For the treatment of ocular diseases, eye drops are the first choice with the most common, economic and good compliance. So we proposed that PNS might be able to treat inflammatory ocular surface diseases by eye drops based on its anti-inflammatory and antioxidant activities. The short elimination half-life (t1/2) and rapid elimination of PNS after oral or intravenous administration may limit its application for eye disorders. Meanwhile, there is a lack of pharmacokinetic study on trace amount of tear samples with PNS eye drops. Therefore, a simple and sensitive ultra-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (UPLC-QqQ-MS/MS) method by multiple reaction monitoring (MRM) in positive ion mode was firstly developed and applied in the pharmacokinetic study of PNS in rabbit tears. Tears samples were prepared by protein precipitation using methanol. The linearity, limit of detection, limit of quantification, specificity, precision, repeatability, stability, recovery, and matrix effect have been investigated and passed their validation criteria. Compared with prior methods, this method has the advantages of rapid analysis, high sensitivity, simple sample preparation and less sample demands. The pharmacokinetic results indicated that PNS eye drops had a slower elimination and a longer t1/2 by topical ocular administration, which is expected to improve the success rate of eye drops in the treatment of anterior segment diseases. The ocular pharmacokinetics of PNS provides an experimental guidance and feasibility basis for in vivo effect verification of PNS eye drops in the future investigation.

Clinical and Genomic Analysis of Patients with Short Survival after Surgery for Esophageal Squamous Cell Carcinoma.

BACKGROUND: This study aimed to investigate the prognosis of Chinese patients with esophageal squamous cell carcinoma (ESCC) after surgery and its correlation with genomic alterations (GAs) to identify potential prognostic markers. METHODS: The clinical information, pathological specimens, and follow-up information of 50 patients with stage II and III primary ESCC who were surgically resected in the Fourth Hospital of Hebei Medical University from January 2011 to December 2015 were collected in the present study. Based on overall survival (OS), these patients were divided into the short OS group (<3 years) and the long OS group (>4 years). GA detection was performed in patients with ESCC using next-generation sequencing. All categories of GAs were evaluated; the landscape of GAs in patients with ESCC was mapped; and the correlations between clinical characteristics, prognosis, and GAs were analyzed. RESULTS: There was no skew in the distribution of gender, smoking, and adjuvant therapy between the long OS group and the short OS group. A total of 372 GAs were detected in the 50 patients with ESCC, with 7 types of GAs, including insertions, deletions, and copy number variations, and missense mutations occurred most frequently, with a frequency of >50.0%. Tumor protein 53 (TP53; 50/50, 100%) was the most commonly mutated gene in the entire cohort followed by cyclin D1, cyclin-dependent kinase inhibitor 2A (CDKN2A), and fibroblast growth factor 19. More CDKN2A loss (p = 0.098) was detected in the short OS group than in the long OS group. The results of the multivariate analysis after adjustment for clinical factors showed a statistically significant difference in the CDKN2A loss between the two groups. Data obtained from The Cancer Genome Atlas for surgical ESCC revealed that the CDKN2A loss may be responsible for the poorer prognosis in postoperative patients with ESCC. CONCLUSION: In patients with progressive primary ESCC, the poor postoperative prognosis may be epiphenomenally associated with the CDKN2A loss.

Moxibustion attenuates inflammation and alleviates axial spondyloarthritis in mice: Possible role of APOE in the inhibition of the Wnt pathway.

Background and aim: Moxibustion is widely used in China and other East Asian countries to manage the symptom of ankylosing spondylitis (AS). This study investigated the effects of moxibustion intervention on protein expression through proteomics analysis in AS mice. Experimental procedure: Proteoglycan-induced spondylitis (PGISp) was established in Balb/c mice. PGISp mice were intervened with daily moxibustion at ST36, BL23, and DU4 for four weeks. Various biochemical (including pro-inflammatory cytokines and bone metabolism indexes) and histopathological parameters were determined. The effects of moxibustion on protein changes in AS mice were analyzed using data-independent acquisition-mass spectrometry (DIA-MS). The target proteins were then confirmed by Western blot analysis. Results: Moxibustion significantly decreased pro-inflammatory cytokine expression including IL-1ß, TNF-α, IL-17, and IL-6, reduced the mRNA expression of RANKL, RANK, ALP, and OCN, and improved the histopathological examination in AS mice. DIA-MS proteomic technique has identified 25 candidate proteins involved in the mechanisms of moxibustion for AS mice, most of which are mainly associated with the regulation of Wnt/ß-catenin. Integrated pathway analysis revealed that glycine, serine and threonine metabolism together with lipid metabolism were the most important canonical pathways involved in the anti-AS effect of moxibustion. In line with the multi-omic data, the levels of BPGM, APOC2, APOE, and GPD1 modified in the AS mice, intervened with moxibustion as confirmed by Western blot. In particular, APOE may play a key role in linking the lipid metabolism and the Wnt/ß-catenin pathway of new bone formation. Conclusion: In conclusion, moxibustion may reduce pro-inflammatory cytokines and improve bone erosion for AS mice. The regulation of APOE by moxibustion may have a potential inhibitory effect on the Wnt/ß-catenin pathway in AS mice. However, due to the lack of silencing or overexpression of key molecules of the signal pathway, whether the beneficial and positive effect of moxibustion involved in the regulation of Wnt/ß-catenin signaling pathway by APOE or other aspects, needed to be explored in further study.

Indocyanine Green Retention Test as a Predictor of Postoperative Complications in Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma.

Background: Accurate preoperative estimation of liver function reserve is the key to the safety of hepatectomy. Recently, indocyanine green retention test at 15 minutes (ICG-R15) has been widely used to estimate hepatic function reserve in different liver diseases. The purpose of this research was to investigate the clinical value of ICG-R15 in predicting postoperative major complications and severe posthepatectomy liver failure (PHLF) in patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) subjected to hepatectomy. Methods: A total of 354 HBV-associated HCC patients who underwent hepatectomy were enrolled. The Child-Pugh, model for end-stage liver disease (MELD), albumin-bilirubin (ALBI) and ICG-R15 for assessing postoperative complications risk were compared using receiver operating characteristic (ROC) curve and decision curve analysis (DCA). Results: Postoperative major complications developed in 32 patients (9.1%) and severe PHLF developed in 57 (16.1%) patients. Multivariate analyses revealed that ICG-R15 were independent factors for predicting postoperative major complications and severe PHLF. ROC curve analyses and DCA plots showed that the predictive abilities of ICG-R15 for postoperative major complications and severe PHLF risk was significantly greater than Child-Pugh, MELD, and ALBI scores. Similar results were obtained by stratifying different background subgroups. Then, patients were divided into three different risk cohorts, emphasizing the significantly discrepancy between the incidence of postoperative major complications and severe PHLF. Conclusion: Compared with Child-Pugh, MELD and ALBI scores, ICG-R15 revealed significantly advantages in predicting postoperative major complications and severe PHLF in HBV-related HCC patients subjected to liver resection.

Developmental artificial neural network model to evaluate the preoperative safe limit of future liver remnant volume for HCC combined with clinically significant portal hypertension.

Background & aims: Finding a way to comprehensively integrate the presence and grade of clinically significant portal hypertension, amount of preserved liver function and extent of hepatectomy into the guidelines for choosing appropriate candidates to hepatectomy remained challenging. This study sheds light on these issues to facilitate precise surgical decisions for clinicians. Methods: Independent risk factors associated with grade B/C post-hepatectomy liver failure were identified by stochastic forest algorithm and logistic regression in hepatitis B virus-related hepatocellular carcinoma patients. Results: The artificial neural network model was generated by integrating preoperative pre-ALB, prothrombin time, total bilirubin, AST, indocyanine green retention rate at 15 min, standard future liver remnant volume and clinically significant portal hypertension grade. In addition, stratification of patients into three risk groups emphasized significant distinctions in the risk of grade B/C post-hepatectomy liver failure. Conclusion: The authors' artificial neural network model could provide a reasonable therapeutic option for clinicians to select optimal candidates with clinically significant portal hypertension for hepatectomy and supplement the hepatocellular carcinoma surgical treatment algorithm.

Hepatectomy involves removing the tumor from the liver and is considered the most effective treatment for hepatocellular carcinoma (HCC). Clinically significant portal hypertension is characterized by the presence of gastric and/or esophageal varices and a platelet count <100 × 10⁹/l with the presence of splenomegaly, which would aggravate the risk of post-hepatectomy liver failure, and is therefore regarded as a contraindication to hepatectomy. Over the past few decades, with improvement in surgical techniques and perioperative care, the morbidity of postoperative complications and mortality have decreased greatly. Current HCC guidelines recommend the expansion of hepatectomy to HCC patients with clinically significant portal hypertension. However, determining how to select optimal candidates for hepatectomy remains challenging. The authors' artificial neural network is a mathematical tool developed by simulating the properties of neurons with large-scale information distribution and parallel structure. Here the authors retrospectively enrolled 871 hepatitis B virus-related HCC patients and developed an artificial neural network model to predict the risk of post-hepatectomy liver failure, which could provide a reasonable therapeutic option and facilitate precise surgical decisions for clinicians.

Preoperative fibrinogen-to-albumin ratio predicts the prognosis of patients with hepatocellular carcinoma subjected to hepatectomy.

BACKGROUND: Systemic inflammatory response (SIR) plays a crucial role in every step of tumorigenesis and development. More recently, the fibrinogen-to-albumin ratio (FAR), an inflammation-based model, was suggested as a prognostic maker for various cancer patients. This research aimed to estimate the prognostic abilities of FAR, neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet- lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) in patients with hepatocellular carcinoma (HCC) subjected to curative hepatectomy. METHODS: A total of 1,502 cases who underwent hepatectomy for HCC were included. The predictive performances of FAR, NLR, MLR, PLR and SII were assessed with regards to overall survival (OS) and disease-free survival (DFS). The area under the time-dependent receiver operating characteristic curve was used to compare prognostic performances. RESULTS: Data revealed that FAR had higher predictive accuracy than other inflammation-based models and alpha-fetoprotein (AFP) in assessing OS and DFS. Indeed, the OS and DFS of patients with high FAR (> 8.9), differentiated by the optimal cut-off value of FAR, were remarkably reduced (p < 0.05 for OS and DFS). Multivariate Cox regression analyses identified that AFP, FAR, clinically significant portal hypertension, tumor size, Barcelona Clinical Liver Cancer staging system, major resection and blood loss were independent indicators for predicting OS and DFS. Furthermore, these patients could be classified according to their FAR into significantly different subgroups, regardless of AFP levels (p < 0.05 for DFS and OS). Similar results were obtained in other inflammation-based prognostic models. CONCLUSIONS: Compared with NLR, MLR, PLR, SII and AFP, FAR showed significant advantages in predicting survival of HCC patients subjected to liver resection.

Artificial neural network model to predict post-hepatectomy early recurrence of hepatocellular carcinoma without macroscopic vascular invasion.

BACKGROUND: The accurate prediction of post-hepatectomy early recurrence (PHER) of hepatocellular carcinoma (HCC) is vital in determining postoperative adjuvant treatment and monitoring. This study aimed to develop and validate an artificial neural network (ANN) model to predict PHER in HCC patients without macroscopic vascular invasion. METHODS: Nine hundred and three patients who underwent curative liver resection for HCC participated in this study. They were randomly divided into derivation (n = 679) and validation (n = 224) cohorts. The ANN model was developed in the derivation cohort and subsequently verified in the validation cohort. RESULTS: PHER morbidity in the derivation and validation cohorts was 34.8 and 39.2%, respectively. A multivariable analysis revealed that hepatitis B virus deoxyribonucleic acid load, γ-glutamyl transpeptidase level, α-fetoprotein level, tumor size, tumor differentiation, microvascular invasion, satellite nodules, and blood loss were significantly associated with PHER. These factors were incorporated into an ANN model, which displayed greater discriminatory abilities than a Cox's proportional hazards model, preexisting recurrence models, and commonly used staging systems for predicting PHER. The recurrence-free survival curves were significantly different between patients that had been stratified into two risk groups. CONCLUSION: When compared to other models and staging systems, the ANN model has a significant advantage in predicting PHER for HCC patients without macroscopic vascular invasion.

Combining Aspartate Aminotransferase-to-Platelet Ratio Index with Future Liver Remnant to Assess Preoperative Hepatic Functional Reserve in Patients with Hepatocellular Carcinoma.

BACKGROUND: Accurate preoperative assessment of hepatic functional reserve is essential for conducting a safe hepatectomy. In recent years, aspartate aminotransferase-to-platelet ratio index (APRI) has been used as a noninvasive model for assessing fibrosis stage, hepatic functional reserve, and prognosis after hepatectomy with a high level of accuracy. The purpose of this research was to evaluate the clinical value of combining APRI with standardized future liver remnant (sFLR) for predicting severe post-hepatectomy liver failure (PHLF) in patients with hepatocellular carcinoma (HCC). METHODS: Six hundred thirty-seven HCC patients who had undergone hepatectomy were enrolled in this study. The performance of the Child-Pugh (CP) grade, model for end-stage liver disease (MELD), APRI, sFLR, and APRI-sFLR in predicting severe PHLF was assessed using the area under the ROC curve (AUC). RESULTS: Severe PHLF was found to have developed in 101 (15.9%) patients. Multivariate logistic analyses identified that prealbumin, cirrhosis, APRI score, sFLR, and major resection were significantly associated with severe PHLF. The AUC values of the CP, MELD, APRI, and sFLR were 0.626, 0.604, 0.725, and 0.787, respectively, indicating that the APRI and sFLR showed significantly greater discriminatory abilities than CP and MELD (P < 0.05 for all). After APRI was combined with sFLR, the AUC value of APRI-sFLR for severe PHLF was 0.816, which greatly improved the prediction accuracy, compared with APRI or sFLR alone (P < 0.05 for all). Stratified analysis using the status of cirrhosis and extent of resection yielded similar results. Moreover, the incidence and grade of PHLF were significantly different among the three risk groups. CONCLUSION: The combination of APRI and sFLR can be considered to be a predictive factor with increased accuracy for severe PHLF in HCC patients, compared with CP grade, MELD, APRI, or sFLR alone.

Metabolomic analysis of biochemical changes in the tissue and urine of proteoglycan-induced spondylitis in mice after treatment with moxibustion.

BACKGROUND: Moxibustion is widely used in East Asian countries to manage the symptom of rheumatic diseases. The aim of this study was to identify potential metabolic profiles of moxibustion on relieving ankylosing spondylitis (AS) mice through UHPLC-Q-TOF/MS metabolomic study. METHODS: Thirty-two female Balb/c mice were randomized into healthy control (HC), AS model, moxibustion at acupuncture points (MA) in AS model, and moxibustion at non-acupuncture points (MNA) AS model groups. Moxibustion was administered daily at GV4, bilateral BL23 and bilateral ST36 acupuncture points for four weeks in the MA group. The overall health status, the thickness of hind paws and the tissue concentrations of IL-1ß, PGE2, IL-6 and TNF-α were assessed. The UHPLC-Q-TOF/MS was used to explore the perturbations of endogenous metabolites in tissue and urine of AS model mice intervened by moxibustion. RESULTS: Compared with the AS group, the overall health status was significantly improved after 4-week moxibustion intervention (p < 0.05). The results also showed that MA significantly reduced the levels of paw thickness and decreased the levels of four cytokines in the tissue (p < 0.01). Thirty-seven endogenous metabolites identified by the OPLS-DA were considered to be contributing to therapeutic effects of moxibustion. Moreover, metabolic pathway analysis further revealed that the identified metabolites were mainly involved in TCA cycle, Lipid metabolism, Amino Acid metabolism, Intestinal flora metabolism and Purine metabolism. CONCLUSIONS: UHPLC-Q-TOF/MS based metabolomics approach, as a novel and powerful tool, can help us to gain the insights into potential mechanisms of action of moxibustion for AS.

Nomogram for prediction of the international study Group of Liver Surgery (ISGLS) grade B/C Posthepatectomy liver failure in HBV-related hepatocellular carcinoma patients: an external validation and prospective application study.

BACKGROUND: To develop a nomogram for predicting the International Study Group of Liver Surgery (ISGLS) grade B/C posthepatectomy liver failure (PHLF) in hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients. METHODS: Patients initially treated with hepatectomy were included. Univariate regression analysis and stochastic forest algorithm were applied to extract the core indicators and reduce redundancy bias. The nomogram was then constructed by using multivariate logistic regression, and validated in internal and external cohorts, and a prospective clinical application. RESULTS: There were 900, 300 and 387 participants in training, internal and external validation cohorts, with the morbidity of grade B/C PHLF were 13.5, 11.0 and 20.2%, respectively. The nomogram was generated by integrating preoperative total bilirubin, platelet count, prealbumin, aspartate aminotransferase, prothrombin time and standard future liver remnant volume, then achieved good prediction performance in training (AUC = 0.868, 95%CI = 0.836-0.900), internal validation (AUC = 0.868, 95%CI = 0.811-0.926) and external validation cohorts (AUC = 0.820, 95%CI = 0.756-0.861), with well-fitted calibration curves. Negative predictive values were significantly higher than positive predictive values in training cohort (97.6% vs. 33.0%), internal validation cohort (97.4% vs. 25.9%) and external validation cohort (94.3% vs. 41.1%), respectively. Patients who had a nomogram score < 169 or ≧169 were considered to have low or high risk of grade B/C PHLF. Prospective application of the nomogram accurately predicted grade B/C PHLF in clinical practise. CONCLUSIONS: The nomogram has a good performance in predicting ISGLS grade B/C PHLF in HBV-related HCC patients and determining appropriate candidates for hepatectomy.

Artificial Neural Network Model for Liver Cirrhosis Diagnosis in Patients with Hepatitis B Virus-Related Hepatocellular Carcinoma.

BACKGROUND: Testing for the presence of liver cirrhosis (LC) is one of the most critical diagnostic and prognostic assessments for patients with hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). More non-invasive tools are needed to diagnose LC but the predictive abilities of current models are still inconclusive. This study aimed to develop and validate a novel and non-invasive artificial neural network (ANN) model for diagnosing LC in patients with HBV-related HCC using routine laboratory serological indicators. METHODS: A total of 1152 HBV-related HCC patients who underwent hepatectomy were included and randomly divided into the training set (n = 864, 75%) and validation set (n = 288, 25%). The ANN model was constructed from the training set using multivariate Logistic regression analysis and then verified in the validation set. RESULTS: The morbidity of LC in the training and validation sets was 41.2% and 46.8%, respectively. Multivariate analysis showed that age, platelet count, prothrombin time and total bilirubin were independent risk factors for LC (P < 0.05). The area under the ROC curve (AUC) analyses revealed that the ANN model had higher predictive accuracy than the Logistic model (ANN: 0.757 vs Logistic: 0.721; P < 0.001), and other scoring systems (ANN: 0.757 vs CP: 0.532, MELD: 0.594, ALBI: 0.575, APRI: 0.621, FIB-4: 0.644, AAR: 0.491, and GPR: 0.604; P < 0.05 for all) in diagnosing LC. Similar results were obtained in the validation set. CONCLUSION: The ANN model has better diagnostic capabilities than other commonly used models and scoring systems in assessing LC risk in patients with HBV-related HCC.

Artificial neural network model for preoperative prediction of severe liver failure after hemihepatectomy in patients with hepatocellular carcinoma.

BACKGROUND: Posthepatectomy liver failure is a worrisome complication after major hepatectomy for hepatocellular carcinoma and is the leading cause of postoperative mortality. Recommendations for hepatectomy for hepatocellular carcinoma are based on the risk of severe posthepatectomy liver failure, and accurately predicting posthepatectomy liver failure risk before undertaking major hepatectomy is of great significance. Thus, herein, we aimed to establish and validate an artificial neural network model to predict severe posthepatectomy liver failure in patients with hepatocellular carcinoma who underwent hemihepatectomy. METHODS: Three hundred and fifty-three patients who underwent hemihepatectomy for hepatocellular carcinoma were included. We randomly divided the patients into a development set (n = 265, 75%) and a validation set (n = 88, 25%). Multivariate logistic analysis facilitated identification of independent variables that we incorporated into the artificial neural network model to predict severe posthepatectomy liver failure in the development set and then verified in the validation set. RESULTS: The morbidity of patients with severe posthepatectomy liver failure in the development and validation sets was 24.9% and 23.9%, respectively. Multivariate analysis revealed that platelet count, prothrombin time, total bilirubin, aspartate aminotransferase, and standardized future liver remnant were all significant predictors of severe posthepatectomy liver failure. Incorporating these factors, the artificial neural network model showed satisfactory area under the receiver operating characteristic curve for the development set of 0.880 (95% confidence interval, 0.836-0.925) and for the validation set of 0.876 (95% confidence interval, 0.801-0.950) in predicting severe posthepatectomy liver failure and achieved well-fitted calibration ability. The predictive performance of the artificial neural network model for severe posthepatectomy liver failure outperformed the traditional logistic regression model and commonly used scoring systems. Moreover, stratification into 3 risk groups highlighted significant differences between the incidences and grades of posthepatectomy liver failure. CONCLUSION: The artificial neural network model accurately predicted the risk of severe posthepatectomy liver failure in patients with hepatocellular carcinoma who underwent hemihepatectomy. Our artificial neural network model might help surgeons identify intermediate and high-risk patients to facilitate earlier interventions.