An aneurysm-specific preconditioning technique for the acceleration of Newton-Krylov method with application in the simulation of blood flows.

In this paper, we develop an algorithm to simulate blood flows in aneurysmal arteries and focus on the construction of robust and efficient multilevel preconditioners to speed up the convergence of both linear and nonlinear solvers. The work is motivated by the observation that in the local aneurysmal region, the flow is often quite complicated with one or more vortices, but in the healthy section of the artery, the principal component of blood flows along the centerline of the artery. Based on this observation, we introduce a novel two-level additive Schwarz method with a mixed-dimensional coarse preconditioner. The key components of the preconditioner include (1) a three-dimensional coarse preconditioner covering the aneurysm; (2) a one-dimensional coarse preconditioner covering the central line of the healthy section of the artery; (3) a collection of three-dimensional overlapping subdomain preconditioners covering the fine meshes of the entire artery; (4) extension/restriction operators constructed by radial basis functions. The blood flow is modeled by the unsteady incompressible Navier-Stokes equations with resistance outflow boundary conditions discretized by a stabilized finite element method on fully unstructured meshes and the second-order backward differentiation formula in time. The resulting large nonlinear algebraic systems are solved by a Newton-Krylov algorithm accelerated by the new preconditioner in two ways: (1) the initial guess of Newton is obtained by solving a linear system defined by the coarse preconditioner; (2) the Krylov solver of the Jacobian system is preconditioned by the new preconditioner. Numerical experiments indicate that the proposed preconditioner is highly effective and robust for complex flows in a patient-specific artery with aneurysm, and it significantly reduces the numbers of linear and nonlinear iterations.

Baseline gut microbiota and metabolome predict durable immunogenicity to SARS-CoV-2 vaccines.

The role of gut microbiota in modulating the durability of COVID-19 vaccine immunity is yet to be characterised. In this cohort study, we collected blood and stool samples of 121 BNT162b2 and 40 CoronaVac vaccinees at baseline, 1 month, and 6 months post vaccination (p.v.). Neutralisation antibody, plasma cytokine and chemokines were measured and associated with the gut microbiota and metabolome composition. A significantly higher level of neutralising antibody (at 6 months p.v.) was found in BNT162b2 vaccinees who had higher relative abundances of Bifidobacterium adolescentis, Bifidobacterium bifidum, and Roseburia faecis as well as higher concentrations of nicotinic acid (Vitamin B) and γ-Aminobutyric acid (P < 0.05) at baseline. CoronaVac vaccinees with high neutralising antibodies at 6 months p.v. had an increased relative abundance of Phocaeicola dorei, a lower relative abundance of Faecalibacterium prausnitzii, and a higher concentration of L-tryptophan (P < 0.05) at baseline. A higher antibody level at 6 months p.v. was also associated with a higher relative abundance of Dorea formicigenerans at 1 month p.v. among CoronaVac vaccinees (Rho = 0.62, p = 0.001, FDR = 0.123). Of the species altered following vaccination, 79.4% and 42.0% in the CoronaVac and BNT162b2 groups, respectively, recovered at 6 months. Specific to CoronaVac vaccinees, both bacteriome and virome diversity depleted following vaccination and did not recover to baseline at 6 months p.v. (FDR < 0.1). In conclusion, this study identified potential microbiota-based adjuvants that may extend the durability of immune responses to SARS-CoV-2 vaccines.

Lower gut abundance of Eubacterium rectale is linked to COVID-19 mortality.

Introduction: Emerging preclinical and clinical studies suggest that altered gut microbiome composition and functions are associated with coronavirus 2019 (COVID- 19) severity and its long-term complications. We hypothesize that COVID-19 outcome is associated with gut microbiome status in population-based settings. Methods: Gut metagenomic data of the adult population consisting of 2871 subjects from 16 countries were obtained from ExperimentHub through R, while the dynamic death data of COVID-19 patients between January 22, 2020 and December 8, 2020 in each country was acquired from Johns Hopkins Coronavirus Resource Center. An adjusted stable mortality rate (SMR) was used to represent these countries' mortality and correlated with the mean relative abundance (mRA) of healthy adult gut microbiome species. Results: After excluding bacterial species with low prevalence (prevalence <0.2 in the included countries), the ß-diversity was significantly higher in the countries with high SMR when compared with those with median or low SMR (p <0.001). We then identified the mRA of two butyrate producers, Eubacterium rectale and Roseburia intestinalis, that were negatively correlated with SMR during the study period. And the reduction of these species was associated with severer COVID-19 manifestation. Conclusion: Population-based microbiome signatures with the stable mortality rate of COVID-19 in different countries suggest that altered gut microbiome composition and functions are associated with mortality of COVID-19.

Reduced Pathogenicity and Transmission Potential of Omicron BA.1 and BA.2 Sublineages Compared with the Early Severe Acute Respiratory Syndrome Coronavirus 2 D614G Variant in Syrian Hamsters.

BACKGROUND: The epidemiological advantage of Omicron variant is evidenced by its rapid spread and the ability to outcompete prior variants. Among Omicron sublineages, early outbreaks were dominated by BA.1, while BA.2 has gained dominance since February 2022. The relative pathogenicity and transmissibility of BA.1 and BA.2 have not been fully defined. METHODS: We compared viral loads and clinical signs in Syrian hamsters after infection with BA.1, BA.2, or D614G variant. A competitive transmission model and next-generation sequencing were used to compare the relative transmission potential of BA.1 and BA.2. RESULTS: BA.1 and BA.2 caused no apparent clinical signs, while D614G caused more than 10% weight loss. Higher viral loads were detected in nasal wash samples and nasal turbinate and lung tissues from BA.1-inoculated hamsters compared with BA.2-inoculated hamsters. No aerosol transmission was observed for BA.1 or BA.2 under the experimental condition in which D614G transmitted efficiently. BA.1 and BA.2 were able to transmit among hamsters via direct contact; however, BA.1 transmitted more efficiently than BA.2 under the competitive transmission model. No recombination was detected from direct contacts exposed simultaneously to BA.1 and BA.2. CONCLUSIONS: Omicron BA.1 and BA.2 demonstrated attenuated pathogenicity and reduced transmission potential in hamsters compared with early SARS-CoV-2 strains.

Predicting Stroke and Mortality in Mitral Regurgitation: A Machine Learning Approach.

We hypothesized that an interpretable gradient boosting machine (GBM) model considering comorbidities, P-wave and echocardiographic measurements, can better predict mortality and cerebrovascular events in mitral regurgitation (MR). Patients from a tertiary center were analyzed. The GBM model was used as an interpretable statistical approach to identify the leading indicators of high-risk patients with either outcome of CVAs and all-cause mortality. A total of 706 patients were included. GBM analysis showed that age, systolic blood pressure, diastolic blood pressure, plasma albumin levels, mean P-wave duration (PWD), MR regurgitant volume, left ventricular ejection fraction (LVEF), left atrial dimension at end-systole (LADs), velocity-time integral (VTI) and effective regurgitant orifice were significant predictors of TIA/stroke. Age, sodium, urea and albumin levels, platelet count, mean PWD, LVEF, LADs, left ventricular dimension at end systole (LVDs) and VTI were significant predictors of all-cause mortality. The GBM demonstrates the best predictive performance in terms of precision, sensitivity c-statistic and F1-score compared to logistic regression, decision tree, random forest, support vector machine, and artificial neural networks. Gradient boosting model incorporating clinical data from different investigative modalities significantly improves risk prediction performance and identify key indicators for outcome prediction in MR.

3'untranslated regions of tumor suppressor genes evolved specific features to favor cancer resistance.

Cancer-related genes have evolved specific genetic and genomic features to favor tumor suppression. Previously we reported that tumor suppressor genes (TSGs) acquired high promoter CpG dinucleotide frequencies during evolution to maintain high expression in normal tissues and resist cancer-specific downregulation. In this study, we investigated whether 3'untranslated regions (3'UTRs) of TSGs have evolved specific features to carry out similar functions. We found that 3'UTRs of TSGs, especially those involved in multiple histological types and pediatric cancers, are longer than those of non-cancer genes. 3'UTRs of TSGs also exhibit higher density of binding sites for RNA-binding proteins (RBPs), particularly those having high affinities to C-rich motifs. Both longer 3'UTR length and RBP binding sites enrichment are correlated with higher gene expression in normal tissues across tissue types. Moreover, both features together with the correlated N6-methyladenosine modification and the extent of protein-protein interactions are positively associated with the ability of TSGs to resist cancer-specific downregulation. These results were successfully validated with independent datasets. Collectively, these findings indicate that TSGs have evolved longer 3'UTR with increased propensity to RBP binding, N6-methyladenosine modification and protein-protein interactions for optimizing their tumor-suppressing functions.

Intraoperative Inspiratory Oxygen Fraction and Myocardial Injury After Noncardiac Surgery: Results From an International Observational Study in Relation to Recent Controlled Trials.

BACKGROUND: Two trials reported that a high inspiratory oxygen fraction (F io2 ) does not promote myocardial infarction or death. Observational studies can provide larger statistical strength, but associations can be due to unobserved confounding. Therefore, we evaluated the association between intraoperative F io2 and cardiovascular complications in a large international cohort study to see if spurious associations were observed. METHODS: We included patients from the Vascular events In noncardiac Surgery patIents cOhort evaluatioN (VISION) study, who were ≥45 years of age, scheduled for overnight hospital admission, and had intraoperative F io2 recorded. The primary outcome was myocardial injury after noncardiac surgery (MINS), and secondary outcomes included mortality and pneumonia, all within 30 postoperative days. Data were analyzed with logistic regression, adjusted for many baseline cardiovascular risk factors, and illustrated in relation to findings from 2 recent controlled trials. RESULTS: We included 6588 patients with mean age of 62 years of whom 49% had hypertension. The median intraoperative F io2 was 0.46 (5%-95% range, 0.32-0.94). There were 808 patients (12%) with MINS. Each 0.10 increase in median F io2 was associated with a confounder-adjusted increase in odds for MINS: odds ratio (OR), 1.17 (95% confidence interval [CI], 1.12-1.23; P < .0001). MINS occurred in contrast with similar frequencies and no significant difference in controlled trials (2240 patients, 194 events), in which patients were given 80% vs 30% oxygen. Mortality was 2.4% and was not significantly associated with a median F io2 (OR, 1.07; 95% CI, 0.97-1.19 per 0.10 increase; P = .18), and 2.9% of patients had pneumonia (OR, 1.05; 95% CI, 0.95-1.15 per 0.10 increase; P = .34). CONCLUSIONS: We observed an association between intraoperative F io2 and risk of myocardial injury within 30 days after noncardiac surgery, which contrasts with recent controlled clinical trials. F io2 was not significantly associated with mortality or pneumonia. Unobserved confounding presumably contributed to the observed association between F io2 and myocardial injury that is not supported by trials.

Stress Hyperglycemia Is Associated With an Increased Risk of Subsequent Development of Diabetes Among Bacteremic and Nonbacteremic Patients.

OBJECTIVE: Stress hyperglycemia is associated with an increased risk of diabetes among survivors of critical illness. We investigated whether patients without diabetes hospitalized for bacteremia or nonbacteremic diseases with transient stress hyperglycemia would have a higher risk of subsequent diabetes development compared with those who remained normoglycemic. RESEARCH DESIGN AND METHODS: This retrospective observational study was conducted on 224,534 in-patients with blood culture records. Stress hyperglycemia was defined based on the highest random glucose level ≥7.8 mmol/L during the index admission period. Diagnosis of diabetes, as the primary end point of interest, was defined based on diagnostic codes, blood test results, or medication records. Differences in cumulative incidence and hazard ratios (HRs) of diabetes between groups were assessed using the Kaplan-Meier estimator and Cox regression. RESULTS: After exclusion of patients with preexisting or undiagnosed diabetes or indeterminate diabetes status and propensity score matching, bacteremic patients with stress hyperglycemia had a significantly higher cumulative incidence of diabetes (HR 1.7, 95% CI 1.2-2.4) compared with those who remained normoglycemic. Stress hyperglycemia was further confirmed to be a diabetes predictor independent of age, sex, comorbidity, and other serological markers. For the nonbacteremic patients, stress hyperglycemia was similarly associated with a higher cumulative incidence of diabetes (HR 1.4, 95% CI 1.2-1.7). CONCLUSIONS: Hospitalized patients with transient stress hyperglycemia had a higher risk of subsequent diabetes development compared with their normoglycemic counterparts. Recognition of an increased risk of diabetes in these patients can allow early detection and monitoring in their subsequent follow-ups.

Gut microbiota composition is associated with SARS-CoV-2 vaccine immunogenicity and adverse events.

OBJECTIVE: The gut microbiota plays a key role in modulating host immune response. We conducted a prospective, observational study to examine gut microbiota composition in association with immune responses and adverse events in adults who have received the inactivated vaccine (CoronaVac; Sinovac) or the mRNA vaccine (BNT162b2; BioNTech; Comirnaty). DESIGN: We performed shotgun metagenomic sequencing in stool samples of 138 COVID-19 vaccinees (37 CoronaVac and 101 BNT162b2 vaccinees) collected at baseline and 1 month after second dose of vaccination. Immune markers were measured by SARS-CoV-2 surrogate virus neutralisation test and spike receptor-binding domain IgG ELISA. RESULTS: We found a significantly lower immune response in recipients of CoronaVac than BNT162b2 vaccines (p<0.05). Bifidobacterium adolescentis was persistently higher in subjects with high neutralising antibodies to CoronaVac vaccine (p=0.023) and their baseline gut microbiome was enriched in pathways related to carbohydrate metabolism (linear discriminant analysis (LDA) scores >2 and p<0.05). Neutralising antibodies in BNT162b2 vaccinees showed a positive correlation with the total abundance of bacteria with flagella and fimbriae including Roseburia faecis (p=0.028). The abundance of Prevotella copri and two Megamonas species were enriched in individuals with fewer adverse events following either of the vaccines indicating that these bacteria may play an anti-inflammatory role in host immune response (LDA scores>3 and p<0.05). CONCLUSION: Our study has identified specific gut microbiota markers in association with improved immune response and reduced adverse events following COVID-19 vaccines. Microbiota-targeted interventions have the potential to complement effectiveness of COVID-19 vaccines.

SARS-CoV-2 non-structural protein 6 triggers NLRP3-dependent pyroptosis by targeting ATP6AP1.

A recent mutation analysis suggested that Non-Structural Protein 6 (NSP6) of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is a key determinant of the viral pathogenicity. Here, by transcriptome analysis, we demonstrated that the inflammasome-related NOD-like receptor signaling was activated in SARS-CoV-2-infected lung epithelial cells and Coronavirus Disease 2019 (COVID-19) patients' lung tissues. The induction of inflammasomes/pyroptosis in patients with severe COVID-19 was confirmed by serological markers. Overexpression of NSP6 triggered NLRP3/ASC-dependent caspase-1 activation, interleukin-1ß/18 maturation, and pyroptosis of lung epithelial cells. Upstream, NSP6 impaired lysosome acidification to inhibit autophagic flux, whose restoration by 1α,25-dihydroxyvitamin D3, metformin or polydatin abrogated NSP6-induced pyroptosis. NSP6 directly interacted with ATP6AP1, a vacuolar ATPase proton pump component, and inhibited its cleavage-mediated activation. L37F NSP6 variant, which was associated with asymptomatic COVID-19, exhibited reduced binding to ATP6AP1 and weakened ability to impair lysosome acidification to induce pyroptosis. Consistently, infection of cultured lung epithelial cells with live SARS-CoV-2 resulted in autophagic flux stagnation, inflammasome activation, and pyroptosis. Overall, this work supports that NSP6 of SARS-CoV-2 could induce inflammatory cell death in lung epithelial cells, through which pharmacological rectification of autophagic flux might be therapeutically exploited.

The impact of IPACK combined with adductor canal block under ultrasound guidance on early motor function after total knee arthroplasty.

BACKGROUND: This study aimed to evaluate the impact of Infiltration between the Popliteal Artery and Capsule of the posterior Knee (IPACK) combined with an adductor canal block under the guidance of ultrasound on early motor function after Total Knee Arthroplasty (TKA). METHODS: A sample of 60 cases who were scheduled for elective unilateral TKA were divided into two groups using random number table method: a group with IPACK combined with an adductor canal block (I group, n = 30), and a group with femoral nerve block combined with superior popliteal sciatic nerve block (FS group, n = 30). Before anesthesia induction was completed, the patients in I group received an ultrasound-guided adductor canal block with 15 mL of 0.375% ropivacaine and an IPACK block with 25 mL of ropivacaine, and the patients in FS group received a femoral nerve block and a superior popliteal sciatic nerve block with 20 mL of 0.375% ropivacaine under ultrasound guidance. Post-operation, all the patients received patient-controlled intravenous analgesia combined with an oral celecoxib capsule to relieve pain and maintain a visual analogue scale score of ≤ 3. RESULTS: The quadriceps femoris muscle strength score was significantly higher in Ⅰ group than in FS group (p = 0.001), while the modified Bromage score were significantly lower and walking distance results were significantly higher in Ⅰ group than in FS group (both p = 0.000). CONCLUSION: Compared with femoral nerve block combined with superior popliteal sciatic nerve block, IPACK combined with adductor canal block had a mild impact on early motor functions after TKA.

Clinical Characteristics, Treatment Effectiveness, and Predictors of Response to Pharmacotherapeutic Interventions Among Patients with Herpetic-Related Neuralgia: A Retrospective Analysis.

BACKGROUND: The treatment for herpetic-related neuralgia focuses on symptom control by use of antiviral drugs, anticonvulsants, and tricyclic antidepressants. We aimed to explore the clinical characteristics associated with medication responsiveness, and to build a classifier for identification of patients who have risk of inadequate pain management. METHODS: We recruited herpetic-related neuralgia patients during a 3-year period. Patients were stratified into a medication-resistant pain (MRP) group when the pain decrease in the visual analogue scale (VAS) is < 3 points, and otherwise a medication-sensitive pain (MSP) group. Multivariate logistic regression was performed to determine the factors associated with MRP. We fitted four machine learning (ML) models, namely logistic regression, random forest, supporting vector machines (SVM), and naïve Bayes with clinical characteristics gathered at admission to identify patients with MRP. RESULTS: A total of 213 patients were recruited, and 132 (61.97%) patients were diagnosed with MRP. Subacute herpes zoster (HZ) (vs. acute, OR 8.95, 95% CI 3.15-29.48, p = 0.0001), severe lesion (vs. mild lesion, OR 3.84, 95% CI 1.44-10.81, p = 0.0084), depressed mood (unit increase OR 1.10, 95% CI 1.00-1.20, p = 0.0447), and hypertension (hypertension, vs. no hypertension, OR 0.36, 95% CI 0.14-0.87, p = 0.0266) were significantly associated with MRP. Among four ML models, SVM had the highest accuracy (0.917) and receiver operating characteristic-area under the curve (0.918) to discriminate MRP from MSP. Phase of disease is the most important feature when fitting ML models. CONCLUSIONS: Clinical characteristics collected before treatment could be adopted to identify patients with MRP.

Outcomes of respiratory viral-bacterial co-infection in adult hospitalized patients.

BACKGROUND: Viral infections of the respiratory tract represent a major global health concern. Co-infection with bacteria may contribute to severe disease and increased mortality in patients. Nevertheless, viral-bacterial co-infection patterns and their clinical outcomes have not been well characterized to date. This study aimed to evaluate the clinical features and outcomes of patients with viral-bacterial respiratory tract co-infections. METHODS: We included 19,361 patients with respiratory infection due to respiratory viruses [influenza A and B, respiratory syncytial virus (RSV), parainfluenza] and/or bacteria in four tertiary hospitals in Hong Kong from 2013 to 2017 using a large territory-wide healthcare database. All microbiological tests were conducted within 48 h of hospital admission. Four etiological groups were included: (1) viral infection alone; (2) bacterial infection alone; (3) laboratory-confirmed viral-bacterial co-infection and (4) clinically suspected viral-bacterial co-infection who were tested positive for respiratory virus and negative for bacteria but had received at least four days of antibiotics. Clinical features and outcomes were recorded for laboratory-confirmed viral-bacterial co-infection patients compared to other three groups as control. The primary outcome was 30-day mortality. Secondary outcomes were intensive care unit (ICU) admission and length of hospital stay. Propensity score matching estimated by binary logistic regression was used to adjust for the potential bias that may affect the association between outcomes and covariates. FINDINGS: Among 15,906 patients with respiratory viral infection, there were 8451 (53.1%) clinically suspected and 1,087 (6.8%) laboratory-confirmed viral-bacterial co-infection. Among all the bacterial species, Haemophilus influenzae (226/1,087, 20.8%), Pseudomonas aeruginosa (180/1087, 16.6%) and Streptococcus pneumoniae (123/1087, 11.3%) were the three most common bacterial pathogens in the laboratory-confirmed co-infection group. Respiratory viruses co-infected with non-pneumococcal streptococci or methicillin-resistant Staphylococcus aureus was associated with the highest death rate [9/30 (30%) and 13/48 (27.1%), respectively] in this cohort. Compared with other infection groups, patients with laboratory-confirmed co-infection had higher ICU admission rate (p < 0.001) and mortality rate at 30 days (p = 0.028), and these results persisted after adjustment for potential confounders using propensity score matching. Furthermore, patients with laboratory-confirmed co-infection had significantly higher mortality compared to patients with bacterial infection alone. INTERPRETATION: In our cohort, bacterial co-infection is common in hospitalized patients with viral respiratory tract infection and is associated with higher ICU admission rate and mortality. Therefore, active surveillance for bacterial co-infection and early antibiotic treatment may be required to improve outcomes in patients with respiratory viral infection.

Spatially and Reversibly Actuating Soft Gel Structure by Harnessing Multimode Elastic Instabilities.

Autonomous shape transformation is key in developing high-performance soft robotics technology; the search for pronounced actuation mechanisms is an ongoing mission. Here, we present the programmable shape morphing of a three-dimensional (3D) curved gel structure by harnessing multimode mechanical instabilities during free swelling. First of all, the coupling of buckling and creasing occurs at the dedicated region of the gel structure, which is attributed to the edge and surface instabilities resulted from structure-defined spatial nonuniformity of swelling. The subsequent developments of post-buckling morphologies and crease patterns collaboratively drive the structural transformation of the gel part from the "open" state to the "closed" state, thus realizing the function of gripping. By utilizing the multi-stimuli-responsive nature of the hydrogel, we recover the swollen gel structure to its initial state, enabling reproducible and cyclic shape evolution. The described soft gel structure capable of shape transformation brings a variety of advantages, such as easy to fabricate, large strain transformation, efficient actuation, and high strength-to-weight ratio, and is anticipated to provide guidance for future applications in soft robotics, flexible electronics, offshore engineering, and healthcare products.

Multi-omic analysis suggests tumor suppressor genes evolved specific promoter features to optimize cancer resistance.

Tumor suppressor genes (TSGs) exhibit distinct evolutionary features. We speculated that TSG promoters could have evolved specific features that facilitate their tumor-suppressing functions. We found that the promoter CpG dinucleotide frequencies of TSGs are significantly higher than that of non-cancer genes across vertebrate genomes, and positively correlated with gene expression across tissue types. The promoter CpG dinucleotide frequencies of all genes gradually increase with gene age, for which young TSGs have been subject to a stronger evolutionary pressure. Transcription-related features, namely chromatin accessibility, methylation and ZNF263-, SP1-, E2F4- and SP2-binding elements, are associated with gene expression. Moreover, higher promoter CpG dinucleotide frequencies and chromatin accessibility are positively associated with the ability of TSGs to resist downregulation during tumorigenesis. These results were successfully validated with independent datasets. In conclusion, TSGs evolved specific promoter features that optimized cancer resistance through achieving high expression in normal tissues and resistance to downregulation during tumorigenesis.

Lysosome activation in peripheral blood mononuclear cells and prognostic significance of circulating LC3B in COVID-19.

Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide, causing significant mortality. There is a mechanistic relationship between intracellular coronavirus replication and deregulated autophagosome-lysosome system. We performed transcriptome analysis of peripheral blood mononuclear cells (PBMCs) from COVID-19 patients and identified the aberrant upregulation of genes in the lysosome pathway. We further determined the capability of two circulating markers, namely microtubule-associated proteins 1A/1B light chain 3B (LC3B) and (p62/SQSTM1) p62, both of which depend on lysosome for degradation, in predicting the emergence of moderate-to-severe disease in COVID-19 patients requiring hospitalization for supplemental oxygen therapy. Logistic regression analyses showed that LC3B was associated with moderate-to-severe COVID-19, independent of age, sex and clinical risk score. A decrease in LC3B concentration <5.5 ng/ml increased the risk of oxygen and ventilatory requirement (adjusted odds ratio: 4.6; 95% CI: 1.1-22.0; P = 0.04). Serum concentrations of p62 in the moderate-to-severe group were significantly lower in patients aged 50 or below. In conclusion, lysosome function is deregulated in PBMCs isolated from COVID-19 patients, and the related biomarker LC3B may serve as a novel tool for stratifying patients with moderate-to-severe COVID-19 from those with asymptomatic or mild disease. COVID-19 patients with a decrease in LC3B concentration <5.5 ng/ml will require early hospital admission for supplemental oxygen therapy and other respiratory support.

Hypozincemia in COVID-19 Patients Correlates With Stronger Antibody Response.

Zinc ion as an enzyme cofactor exhibits antiviral and anti-inflammatory activity during infection, but circulating zinc ion level during Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection is unclear. This study aimed to evaluate serum zinc ion level in Coronavirus Disease 2019 (COVID-19) patients and healthy subjects, as well as its correlation with antibodies against SARS-CoV-2. 114 COVID-19 patients and 48 healthy subjects (38 healthy volunteers and 10 close contacts of patients with COVID-19) were included. Zinc ion concentration and levels of antibodies against SARS-CoV-2 Spike 1 + Spike 2 proteins, nucleocapsid protein, and receptor-binding domain in serum were measured. Results showed that the concentration of zinc ion in serum from COVID-19 patients [median: 6.4 nmol/mL (IQR 1.5 - 12.0 nmol/mL)] were significantly lower than that from the healthy subjects [median: 15.0 nmol/mL (IQR 11.9 - 18.8 nmol/mL)] (p < 0.001) and the difference remained significant after age stratification (p < 0.001) or when the patients were at the recovery stage (p < 0.001). Furthermore, COVID-19 patients with more severe hypozincemia showed higher levels of IgG against the receptor-binding domain of SARS-CoV-2 spike protein. Further studies to confirm the effect of zinc supplementation on improving the outcomes of COVID-19, including antibody response against SARS-CoV-2, are warranted.

Multi-modality machine learning approach for risk stratification in heart failure with left ventricular ejection fraction ≤ 45.

AIMS: Heart failure (HF) involves complex remodelling leading to electrical and mechanical dysfunction. We hypothesized that machine learning approaches incorporating data obtained from different investigative modalities including atrial and ventricular measurements from electrocardiography and echocardiography, blood inflammatory marker [neutrophil-to-lymphocyte ratio (NLR)], and prognostic nutritional index (PNI) will improve risk stratification for adverse outcomes in HF compared to logistic regression. METHODS AND RESULTS: Consecutive Chinese patients referred to our centre for transthoracic echocardiography and subsequently diagnosed with HF, between 1 January 2010 and 31 December 2016, were included in this study. Two machine learning techniques, multilayer perceptron and multi-task learning, were compared with logistic regression for their ability to predict incident atrial fibrillation (AF), transient ischaemic attack (TIA)/stroke, and all-cause mortality. This study included 312 HF patients [mean age: 64 (55-73) years, 75% male]. There were 76 cases of new-onset AF, 62 cases of incident TIA/stroke, and 117 deaths during follow-up. Univariate analysis revealed that age, left atrial reservoir strain (LARS) and contractile strain (LACS) were significant predictors of new-onset AF. Age and smoking predicted incident stroke. Age, hypertension, type 2 diabetes mellitus, chronic kidney disease, mitral or aortic regurgitation, P-wave terminal force in V1, the presence of partial inter-atrial block, left atrial diameter, ejection fraction, global longitudinal strain, serum creatinine and albumin, high NLR, low PNI, and LARS and LACS predicted all-cause mortality. Machine learning techniques achieved better prediction performance than logistic regression. CONCLUSIONS: Multi-modality assessment is important for risk stratification in HF. A machine learning approach provides additional value for improving outcome prediction.

Multi-parametric system for risk stratification in mitral regurgitation: A multi-task Gaussian prediction approach.

BACKGROUND: We hypothesized that a multi-parametric approach incorporating medical comorbidity information, electrocardiographic P-wave indices, echocardiographic assessment, neutrophil-to-lymphocyte ratio (NLR) and prognostic nutritional index (PNI) calculated from laboratory data can improve risk stratification in mitral regurgitation (MR). METHODS: Patients diagnosed with mitral regurgitation between 1 March 2005 and 30 October 2018 from a single centre were retrospectively analysed. Outcomes analysed were incident atrial fibrillation (AF), transient ischemic attack (TIA)/stroke and mortality. RESULTS: This study cohort included 706 patients, of whom 171 had normal inter-atrial conduction, 257 had inter-atrial block (IAB) and 266 had AF at baseline. Logistic regression analysis showed that age, hypertension and mean P-wave duration (PWD) were significant predictors of new-onset AF. Low left ventricular ejection fraction (LVEF), abnormal P-wave terminal force in V1 (PTFV1) predicted TIA/stroke. Age, smoking, hypertension, diabetes mellitus, hypercholesterolaemia, ischemic heart disease, secondary mitral regurgitation, urea, creatinine, NLR, PNI, left atrial diameter (LAD), left ventricular end-diastolic dimension, LVEF, pulmonary arterial systolic pressure, IAB, baseline AF and heart failure predicted all-cause mortality. A multi-task Gaussian process learning model demonstrated significant improvement in risk stratification compared to logistic regression and a decision tree method. CONCLUSIONS: A multi-parametric approach incorporating multi-modality clinical data improves risk stratification in mitral regurgitation. Multi-task machine learning can significantly improve overall risk stratification performance.