METHODS: Expression of SPRY genes in human and mice PDAC was analyzed using The Cancer Genome Atlas and Gene Expression Omnibus datasets, and by immunohistochemistry analysis. Gain-of-function, loss-of-function of Spry1 and orthotopic xenograft model were adopted to investigate the function of Spry1 in mice PDAC. Bioinformatics analysis, transwell and flowcytometry analysis were used to identify the effects of SPRY1 on immune cells. Co-immunoprecipitation and K-ras4B G12V overexpression were used to identify molecular mechanism.
RESULTS: SPRY1 expression was remarkably increased in PDAC tissues and positively associated with poor prognosis of PDAC patients. SPRY1 knockdown suppressed tumor growth in mice. SPRY1 was found to promote CXCL12 expression and facilitate neutrophil and macrophage infiltration via CXCL12-CXCR4 axis. Pharmacological inhibition of CXCL12-CXCR4 largely abrogated the oncogenic functions of SPRY1 by suppressing neutrophil and macrophage infiltration. Mechanistically, SPRY1 interacted with ubiquitin carboxy-terminal hydrolase L1 to induce activation of nuclear factor κB signaling and ultimately increase CXCL12 expression. Moreover, SPRY1 transcription was dependent on KRAS mutation and was mediated by MAPK-ERK signaling.
CONCLUSION: High expression of SPRY1 can function as an oncogene in PDAC by promoting cancer-associated inflammation. Targeting SPRY1 might be an important approach for designing new strategy of tumor therapy.
METHODS: The RVA G9P[8] genotype from a diarrhea sample was passaged in MA104 cells. The virus was evaluated by TEM, polyacrylamide gel electrophoresis, and indirect immunofluorescence assay. The complete genome of virus was obtained by RT-PCR and sequencing. The genomic and evolutionary characteristics of the virus were evaluated by nucleic acid sequence analysis with MEGA ver. 5.0.5 and DNASTAR software. The neutralizing epitopes of VP7 and VP4 (VP5* and VP8*) were analyzed using BioEdit ver. 7.0.9.0 and PyMOL ver. 2.5.2.
RESULTS: The RVA N4006 (G9P[8] genotype) was adapted in MA104 cells with a high titer (105.5 PFU/mL). Whole-genome sequence analysis showed N4006 to be a reassortant rotavirus of Wa-like G9P[8] RVA and the NSP4 gene of DS-1-like G2P[4] RVA, with the genotype constellation G9-P[8]-I1-R1-C1-M1-A1-N1-T1-E2-H1 (G9P[8]-E2). Phylogenetic analysis indicated that N4006 had a common ancestor with Japanese G9P[8]-E2 rotavirus. Neutralizing epitope analysis showed that VP7, VP5*, and VP8* of N4006 had low homology with vaccine viruses of the same genotype and marked differences with vaccine viruses of other genotypes.
CONCLUSION: The RVA G9P[8] genotype with the G9-P[8]-I1-R1-C1-M1-A1-N1-T1-E2-H1 (G9P[8]-E2) constellation predominates in China and may originate from reassortment between Japanese G9P[8] with Japanese DS-1-like G2P[4] rotaviruses. The antigenic variation of N4006 with the vaccine virus necessitates an evaluation of the effect of the rotavirus vaccine on G9P[8]-E2 genotype rotavirus.
METHODS: A prospective-retrospective cohort of 985 patients was identified from the APASL-ACLF Research Consortium (AARC) database and the Chinese Study Group. Complications of ACLF (ascites, infection, hepatorenal syndrome, hepatic encephalopathy, upper gastrointestinal bleeding) as well as cirrhosis and the current main prognostic models were measured for their predictive ability for 28- or 90-day mortality.
RESULTS: A total of 709 patients with HBV-ACLF as defined by the AARC criteria were enrolled. Among these HBV-ACLF patients, the cirrhotic group showed significantly higher mortality and complications than the non-cirrhotic group. A total of 36.1% and 40.1% of patients met the European Association for the Study of Liver (EASL)-Chronic Liver Failure consortium (CLIF-C) criteria in the non-cirrhotic and cirrhotic groups, respectively; these patients had significantly higher rates of mortality and complications than those who did not satisfy the CLIF-C criteria. Furthermore, among patients who did not meet the CLIF-C criteria, the cirrhotic group exhibited higher mortality and complication rates than the non-cirrhotic group, without significant differences in organ failure. The Tongji prognostic predictor model score (TPPMs), which set the number of complications as one of the determinants, showed comparable or superior ability to the Chinese Group on the Study of Severe Hepatitis B-ACLF score (COSSH-ACLFs), APASL-ACLF Research Consortium score (AARC-ACLFs), CLIF-C organ failure score (CLIF-C OFs), CLIF-C-ACLF score (CLIF-C-ACLFs), Model for End-Stage Liver Disease score (MELDs) and MELD-sodium score (MELD-Nas) in HBV-ACLF patients, especially in cirrhotic HBV--ACLF patients. Patients with two (OR 4.70, 1.88) or three (OR 8.27, 2.65) complications had a significantly higher risk of 28- or 90-day mortality, respectively.
CONCLUSION: The presence of complications is a major risk factor for mortality in HBV-ACLF patients. TPPM possesses high predictive ability in HBV-ACLF patients, especially in cirrhotic HBV-ACLF patients.
METHODS: A total of 1402 ACLF patients, enrolled in the APASL-ACLF Research Consortium (AARC) with 90-day follow-up, were analyzed. An ACLF score was developed in a derivation cohort (n = 480) and was validated (n = 922).
RESULTS: The overall survival of ACLF patients at 28 days was 51.7%, with a median of 26.3 days. Five baseline variables, total bilirubin, creatinine, serum lactate, INR and hepatic encephalopathy, were found to be independent predictors of mortality, with AUROC in derivation and validation cohorts being 0.80 and 0.78, respectively. AARC-ACLF score (range 5-15) was found to be superior to MELD and CLIF SOFA scores in predicting mortality with an AUROC of 0.80. The point scores were categorized into grades of liver failure (Gr I: 5-7; II: 8-10; and III: 11-15 points) with 28-day cumulative mortalities of 12.7, 44.5 and 85.9%, respectively. The mortality risk could be dynamically calculated as, with each unit increase in AARC-ACLF score above 10, the risk increased by 20%. A score of ≥11 at baseline or persisting in the first week was often seen among nonsurvivors (p = 0.001).
CONCLUSIONS: The AARC-ACLF score is easy to use, dynamic and reliable, and superior to the existing prediction models. It can reliably predict the need for interventions, such as liver transplant, within the first week.
METHODS: We recruited ACLF patients between 2009 and 2020 from APASL-ACLF Research Consortium (AARC). Their clinical data, investigations and organ involvement were serially noted for 90-days and utilized for AI modelling. Data were split randomly into train and validation sets. Multiple AI models, MELD and AARC-Model, were created/optimized on train set. Outcome prediction abilities were evaluated on validation sets through area under the curve (AUC), accuracy, sensitivity, specificity and class precision.
RESULTS: Among 2481 ACLF patients, 1501 in train set and 980 in validation set, the extreme gradient boost-cross-validated model (XGB-CV) demonstrated the highest AUC in train (0.999), validation (0.907) and overall sets (0.976) for predicting 30-day outcomes. The AUC and accuracy of the XGB-CV model (%Δ) were 7.0% and 6.9% higher than the standard day-7 AARC model (p
METHODS: In this single-arm, open-label, phase 3 trial, we recruited patients from 38 sites across China, Thailand, Vietnam, Singapore, and Malaysia, who were chronically infected with HCV genotypes 1-6, and were HCV treatment-naive or treatment-experienced, either without cirrhosis or with compensated cirrhosis. Patients self-administered a combined sofosbuvir (400 mg) and velpatasvir (100 mg) tablet once daily for 12 weeks. The primary efficacy endpoint was sustained virological response, defined as HCV RNA less than 15 IU/mL at 12 weeks after completion of treatment (SVR12), assessed in all patients who received at least one dose of study drug. The primary safety endpoint was the proportion of adverse events leading to premature discontinuation of study drug. This trial is registered with ClinicalTrials.gov, number NCT02671500, and is completed.
FINDINGS: Between April 14, 2016, and June 30, 2017, 375 patients were enrolled in the study, of whom 374 completed the full treatment course and one discontinued treatment. Overall, 362 (97% [95% CI 94-98]) of 375 patients achieved SVR12. Among 42 patients with HCV genotype 3b, all of whom had baseline resistance-associated substitutions in NS5A, 25 (89% [95% CI 72-98]) of 28 patients without cirrhosis and seven (50% [23-77]) of 14 patients with cirrhosis achieved SVR12. The most common adverse events were upper respiratory tract infection (36 [10%] patients) and headache (18 [5%] patients). There were no discontinuations due to adverse events. Serious adverse events were reported in three (1%) patients, none of which was judged to be related to sofosbuvir-velpatasvir treatment.
INTERPRETATION: Consistent with data from other phase 3 studies, single-tablet sofosbuvir-velpatasvir for 12 weeks is an efficacious and safe treatment for Asian patients with chronic HCV infection, but might have lower efficacy in those infected with HCV genotype 3b and with cirrhosis.
FUNDING: Gilead Sciences.
METHODS: Consecutive ACLF patients were monitored for the development of SIRS/sepsis and associated complications and followed till 90 days, liver transplant or death.
RESULTS: Of 561 patients, 201 (35.8%) had no SIRS and 360 (64.2%) had SIRS with or without infection. New onset SIRS and sepsis developed in 74.6% and 8% respectively in a median of 7 (range 4-15) days, at a rate of 11% per day. The cumulative incidence of new SIRS was 29%, 92.8%, and 100% by days 4, 7, and 15. Liver failure, that is, bilirubin > 12 mg/dL (odds ratio [OR] = 2.5 [95% confidence interval {CI} = 1.05-6.19], P = 0.04) at days 0 and 4, and renal failure at day 4 (OR = 6.74 [95%CI = 1.50-13.29], P = 0.01), independently predicted new onset SIRS. Absence of SIRS in the first week was associated with reduced incidence of organ failure (20% vs 39.4%, P = 0.003), as was the 28-day (17.6% vs 36%, P = 0.02) and 90-day (27.5% vs 51%,P = 0.002) mortality. The 90-day mortality was 61.6% in the total cohort and that for those having no SIRS and SIRS at presentation were 42.8% and 65%, respectively (P
METHODOLOGY: One thousand two hundred and sixteen prospectively enrolled patients with ACLF (males 98%, mean age 42.5 ± 9.4 years, mean CTP, MELD and AARC scores of 12 ± 1.4, 29.7 ± 7 and 9.8 ± 2 respectively) from the Asian Pacific Association for the Study of the Liver (APASL) ACLF Research Consortium (AARC) database were analysed retrospectively. Patients with or without metabolic risk factors were compared for severity (CTP, MELD, AARC scores) and day 30 and 90 mortality. Information on overweight/obesity, type 2 diabetes mellitus (T2DM), hypertension and dyslipidaemia were available in 1028 (85%), 1019 (84%), 1017 (84%) and 965 (79%) patients respectively.
RESULTS: Overall, 392 (32%) patients died at day 30 and 528 (43%) at day 90. Overweight/obesity, T2DM, hypertension and dyslipidaemia were present in 154 (15%), 142 (14%), 66 (7%) and 141 (15%) patients, respectively, with no risk factors in 809 (67%) patients. Patients with overweight/obesity had higher MELD scores (30.6 ± 7.1 vs 29.2 ± 6.9, P = .007) and those with dyslipidaemia had higher AARC scores (10.4 ± 1.2 vs 9.8 ± 2, P = .014). Overweight/obesity was associated with increased day 30 mortality (HR 1.54, 95% CI 1.06-2.24, P = .023). None of other metabolic risk factors, alone or in combination, had any impact on disease severity or mortality. On multivariate analysis, overweight or obesity was significantly associated with 30-day mortality (aHR 1.91, 95% CI 1.41-2.59, P
METHODS: Altogether 1021 patients were analyzed for the severity and organ failure at admission to determine transplant eligibility and 28 day survival with or without transplant.
RESULTS: The ACLF cohort [mean age 44 ± 12.2 years, males 81%) was of sick patients; 55% willing for LT at admission, though 63% of them were ineligible due to sepsis or organ failure. On day 4, recovery in sepsis and/or organ failure led to an improvement in transplant eligibility from 37% at baseline to 63.7%. Delay in LT up to 7 days led to a higher incidence of multiorgan failure (p
PATIENTS AND METHODS: Data of 2360 patients from APASL-ACLF Research Consortium (AARC) was analysed. Multivariate logistic regression model (PIRO score) was developed from a derivation cohort (n=1363) which was validated in another prospective multicentric cohort of acute on chronic liver failure patients (n=997).
RESULTS: Factors significant for P component were serum creatinine[(≥2 mg/dL)OR 4.52, 95% CI (3.67-5.30)], bilirubin [(<12 mg/dL,OR 1) vs (12-30 mg/dL,OR 1.45, 95% 1.1-2.63) vs (≥30 mg/dL,OR 2.6, 95% CI 1.3-5.2)], serum potassium [(<3 mmol/LOR-1) vs (3-4.9 mmol/L,OR 2.7, 95% CI 1.05-1.97) vs (≥5 mmol/L,OR 4.34, 95% CI 1.67-11.3)] and blood urea (OR 3.73, 95% CI 2.5-5.5); for I component nephrotoxic medications (OR-9.86, 95% CI 3.2-30.8); for R component,Systemic Inflammatory Response Syndrome,(OR-2.14, 95% CI 1.4-3.3); for O component, Circulatory failure (OR-3.5, 95% CI 2.2-5.5). The PIRO score predicted acute kidney injury with C-index of 0.95 and 0.96 in the derivation and validation cohort. The increasing PIRO score was also associated with mortality (P
METHODS: Prospectively collected data of ACLF patients from APASL-ACLF Research Consortium (AARC) was analyzed for 30-day outcomes. The models evaluated at days 0, 4, and 7 of presentation for 30-day mortality were: AARC (model and score), CLIF-C (ACLF score, and OF score), NACSELD-ACLF (model and binary), SOFA, APACHE-II, MELD, MELD-Lactate, and CTP. Evaluation parameters were discrimination (c-indices), calibration [accuracy, sensitivity, specificity, and positive/negative predictive values (PPV/NPV)], Akaike/Bayesian Information Criteria (AIC/BIC), Nagelkerke-R2, relative prediction errors, and odds ratios.
RESULTS: Thirty-day survival of the cohort (n = 2864) was 64.9% and was lowest for final-AARC-grade-III (32.8%) ACLF. Performance parameters of all models were best at day 7 than at day 4 or day 0 (p 12 had the lowest 30-day survival (5.7%).
CONCLUSIONS: APASL-ACLF is often a progressive disease, and models assessed up to day 7 of presentation reliably predict 30-day mortality. Day-7 AARC model is a statistically robust tool for classifying risk of death and accurately predicting 30-day outcomes with relatively lower prediction errors. Day-7 AARC score > 12 may be used as a futility criterion in APASL-ACLF patients.
METHODS: We identified drugs as precipitants of ACLF among prospective cohort of patients with ACLF from the Asian Pacific Association of Study of Liver (APASL) ACLF Research Consortium (AARC) database. Drugs were considered precipitants after exclusion of known causes together with a temporal association between exposure and decompensation. Outcome was defined as death from decompensation.
RESULTS: Of the 3,132 patients with ACLF, drugs were implicated as a cause in 329 (10.5%, mean age 47 years, 65% men) and other nondrug causes in 2,803 (89.5%) (group B). Complementary and alternative medications (71.7%) were the commonest insult, followed by combination antituberculosis therapy drugs (27.3%). Alcoholic liver disease (28.6%), cryptogenic liver disease (25.5%), and non-alcoholic steatohepatitis (NASH) (16.7%) were common causes of underlying liver diseases. Patients with drug-induced ACLF had jaundice (100%), ascites (88%), encephalopathy (46.5%), high Model for End-Stage Liver Disease (MELD) (30.2), and Child-Turcotte-Pugh score (12.1). The overall 90-day mortality was higher in drug-induced (46.5%) than in non-drug-induced ACLF (38.8%) (P = 0.007). The Cox regression model identified arterial lactate (P < 0.001) and total bilirubin (P = 0.008) as predictors of mortality.
DISCUSSION: Drugs are important identifiable causes of ACLF in Asia-Pacific countries, predominantly from complementary and alternative medications, followed by antituberculosis drugs. Encephalopathy, bilirubin, blood urea, lactate, and international normalized ratio (INR) predict mortality in drug-induced ACLF.
METHODS: We conducted a cross-sectional, observational, retrospective study across 6 continents, 70 countries, and 457 stroke centers. Diagnoses were identified by their ICD-10 codes or classifications in stroke databases.
RESULTS: There were 91,373 stroke admissions in the 4 months immediately before compared to 80,894 admissions during the pandemic months, representing an 11.5% (95% confidence interval [CI] -11.7 to -11.3, p < 0.0001) decline. There were 13,334 IVT therapies in the 4 months preceding compared to 11,570 procedures during the pandemic, representing a 13.2% (95% CI -13.8 to -12.7, p < 0.0001) drop. Interfacility IVT transfers decreased from 1,337 to 1,178, or an 11.9% decrease (95% CI -13.7 to -10.3, p = 0.001). Recovery of stroke hospitalization volume (9.5%, 95% CI 9.2-9.8, p < 0.0001) was noted over the 2 later (May, June) vs the 2 earlier (March, April) pandemic months. There was a 1.48% stroke rate across 119,967 COVID-19 hospitalizations. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection was noted in 3.3% (1,722/52,026) of all stroke admissions.
CONCLUSIONS: The COVID-19 pandemic was associated with a global decline in the volume of stroke hospitalizations, IVT, and interfacility IVT transfers. Primary stroke centers and centers with higher COVID-19 inpatient volumes experienced steeper declines. Recovery of stroke hospitalization was noted in the later pandemic months.