Miracle-dz/UniFAR-FTUs huggingface dataset:
Rapamycin inhibits hepatitis B virus covalently closed circular DNA transcription by enhancing the ubiquitination of HBx

Hepatitis B virus (HBV) infection is still a serious public health problem worldwide. Antiviral therapies such as interferon and nucleos(t)ide analogs efficiently control HBV replication, but they cannot eradicate chronic hepatitis B (CHB) because of their incapacity to eliminate endocellular covalently closed circular DNA (cccDNA). Thus, there is a necessity to develop new strategies for targeting cccDNA. As cccDNA is difficult to clear, transcriptional silencing of cccDNA is a possible effective strategy. HBx plays a vitally important role in maintaining the transcriptional activity of cccDNA and it could be a target for blocking the transcription of cccDNA. To screen new drugs that may contribute to antiviral therapy, the ability of 2,000 small-molecule compounds to inhibit HBx was examined by the HiBiT lytic detection system. We found that the macrolide compound rapamycin, which is clinically used to prevent acute rejection after organ transplantation, could significantly reduce HBx protein expression. Mechanistic studies demonstrated that rapamycin decreased the stability of the HBx protein by promoting its degradation via the ubiquitin-proteasome system. Moreover, rapamycin inhibited HBV RNA, HBV DNA, and cccDNA transcription levels in HBV-infected cells. In addition, HBx deficiency abrogated the inhibition of cccDNA transcription induced by rapamycin. Similar results were also confirmed in a recombinant cccDNA mouse model. In summary, we report a new small-molecule, rapamycin, which targets HBx to block HBV cccDNA transcription and inhibit HBV replication. This approach can identify new strategies to cure CHB.
Elevation of enterococcus-specific antibodies associated with bacterial translocation is predictive of survival rate in chronic liver disease

Introduction/purpose The gut-liver axis contributes to disease progression, a rise in infection rate, organ failure and a poor overall outcome in chronic liver diseases (CLD). Monitoring of the gut-liver axis is critical in understanding disease status, but biomarkers have not been elucidated. The aim of this study is to determine the level of serum antibodies against Enterococcus (E.) faecalis in evaluating patients with CLD, including those treated with rifaximin (a minimally absorbed antibiotic), and in patients with alcohol-associated liver disease (ALD). Materials and methods We enrolled 109 CLD patients (cohort 1), 30 hepatic encephalopathy patients treated with rifaximin (cohort 2), 53 inpatients with ALD undergoing alcohol cessation (cohort 3) and 33 healthy subjects. To assess the consequences of E. faecalis translocation, we developed an assay for the detection of a serum antibody against E. faecalis capsular polysaccharide (E.CPS). Results Serum E.CPS antibody titer was elevated only in those patients with advanced CLD and ALD. The E.CPS antibody titer was an independent prognostic factor (p < 0.05), while Mac-2 binding protein and albumin-bilirubin score were not independent predictors of survival. The improvement of predictive model in integrated factors was significant [continuous net reclassification index (value 0.699, p < 0.05) and integrated discrimination improvement (value 0.164, p = 0.051)]. Furthermore, rifaximin treatment led to a decrease of serum E.CPS antibody titer resulting in a significantly longer overall rate of survival. Conclusion The E.CPS antibody titer appears to be a strong predictor of survival in CLD patients. Serum E.CPS levels decrease in CLD patients receiving rifaximin, and may be associated with an overall improvement in rate of survival.
Correlating biodegradation kinetics of 2,3,7,8-tetrachlorodibenzo-p-dioxin to the dynamics of microbial communities originating from soil in Vietnam contaminated with herbicides and dioxins

We studied the succession of bacterial communities during the biodegradation of 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD). The communities originated from a mesocosm with soil from Bien Hoa airbase in Vietnam heavily contaminated with herbicides and dioxins. They were grown in defined media with different carbon and Gibbs energy sources and 2,3,7,8-TCDD. Cultures with dimethyl sulfoxide (DMSO) as the sole carbon and energy source degraded about 95% of 2,3,7,8-TCDD within 60 days of cultivation. Those with an additional 1 mM of vanillin did that in roughly 90 days. Further 16S rRNA gene amplicon sequencing showed that the increase in relative abundance of members belonging to the genera Bordetella, Sphingomonas, Proteiniphilum, and Rhizobium correlated to increased biodegradation of 2,3,7,8-TCDD in these cultures. A higher concentration of vanillin slowed down the biodegradation rate. Addition of alternative carbon and Gibbs energy sources, such as amino acids, sodium lactate and sodium acetate, even stopped the degradation of 2,3,7,8-TCDD completely. Bacteria from the genera Bordetella, Achromobacter, Sphingomonas and Pseudomonas dominated most of the cultures, but the microbial profiles also significantly differed between cultures as judged by non-metric multidimensional scaling (NMDS) analyses. Our study indicates that 2,3,7,8-TCDD degradation may be stimulated by bacterial communities preadapted to a certain degree of starvation with respect to the carbon and energy source. It also reveals the succession and abundance of defined bacterial genera in the degradation process.
Facile synthesis of nanosized Mn3O4 powder anodes for high capacity Lithium-Ion battery via flame spray pyrolysis

Mn3O4 powders with nanometer size are successfully synthesized by a simple one-step method via flame spray pyrolysis. The precursor droplet is generated by heating under high temperature flame with fixed flow rate, and the exothermic reaction is induced to form nanosized Mn3O4 powders. When used as anode material for lithium-ion battery, the Mn3O4 exhibits good cycling capacity and rate performance. It delivers a specific capacity of 1,182 mA h g−1 over 110 cycles at a current density of 200 mA g−1, and has a high capacity of 140 mA h g−1 at 5,000 mA g−1.
An enhanced level of VCAM in transplant preservation fluid is an independent predictor of early kidney allograft dysfunction

Background We aimed to evaluate whether donor-related inflammatory markers found in kidney transplant preservation fluid can associate with early development of kidney allograft dysfunction. Methods Our prospective study enrolled 74 consecutive donated organs who underwent kidney transplantation in our center between September 2020 and June 2021. Kidneys from 27 standard criteria donors were allocated to static cold storage and kidneys from 47 extended criteria donors to hypothermic machine perfusion. ELISA assessment of inflammatory biomarkers (IL-6, IL6-R, ICAM, VCAM, TNFα, IFN-g, CXCL1 and Fractalkine) was analyzed in view of a primary endpoint defined as the occurrence of delayed graft function or slow graft function during the first week following transplantation. Results Soluble VCAM levels measured in transplant conservation fluid were significantly associated with recipient serum creatinine on day 7. Multivariate stepwise logistic regression analysis identified VCAM as an independent non-invasive predictor of early graft dysfunction, both at 1 week (OR: 3.57, p = .04, 95% CI: 1.06-12.03) and 3 Months (OR: 4.039, p = .034, 95% CI: 1.11-14.73) after transplant surgery. Conclusions This prospective pilot study suggests that pre-transplant evaluation of VCAM levels could constitute a valuable indicator of transplant health and identify the VCAM-CD49d pathway as a target to limit donor-related vascular injury of marginal transplants.
Phenotypic and functional analysis of γδ T cells in the pathogenesis of human T-cell lymphotropic virus type 1 infection

The human T-cell leukemia virus type 1 (HTLV-1) is the cause of serious malignant and inflammatory diseases, including adult T-cell leukemia and lymphoma and tropical spastic paraparesis. The potential protective role of γδ T cells in HTLV-1 infection remains unclear. Here, demonstrate that there is a decrease in the amount of Vγ9Vδ2 T cells in patients with HTLV-1, especially in those with HTLV-1 associated pathologies. This suggests that γδ T cells could be involved in controlling the virus. Indeed, we found that Vγ9Vδ2 T cells, expanded from non-infected individuals, can kill cells expressing the viral proteins HBZ and Tax and this phenotype is reversed in the presence of mevastatin. Cytotoxicity by Vγ9Vδ2 T cells was not associated with an increase of INF-γ production. In sharp contrast, killing by NK cells was reduced by Tax expression. Thus, our study provides initial evidence for a potential protective role of Vγ9Vδ2 T cells against HTLV-1 infection. Therapeutic exploitation of these insights is feasible with current technologies of T-cell therapies and could provide novel tools to prevent and treat HTLV-1-associated malignancies and neurologic complications.
CT perfusion-based delta-radiomics models to identify collateral vessel formation after revascularization in patients with moyamoya disease

Purpose To build CT perfusion (CTP)-based delta-radiomics models to identify collateral vessel formation after revascularization in patients with moyamoya disease (MMD). Methods Fifty-three MMD patients who underwent CTP and digital subtraction angiography (DSA) examination were retrospectively enrolled. Patients were divided into good and poor groups based on postoperative DSA. CTP parameters, such as mean transit time (MTT), time to drain (TTD), time to maximal plasma concentration (Tmax), and flow extraction product (FE), were obtained. CTP efficacy in evaluating surgical treatment were compared between the good and poor groups. The changes in the relative CTP parameters (ΔrMTT, ΔrTTD, ΔrTmax, and ΔrFE) were calculated to evaluate the differences between pre- and postoperative CTP values. CTP parameters were selected to build delta-radiomics models for identifying collateral vessel formation. The identification performance of machine learning classifiers was assessed using area under the receiver operating characteristic curve (AUC). Results Of the 53 patients, 36 (67.9%) and 17 (32.1%) were divided into the good and poor groups, respectively. The postoperative changes of ΔrMTT, ΔrTTD, ΔrTmax, and ΔrFE in the good group were significantly better than the poor group (p < 0.05). Among all CTP parameters in the perfusion improvement evaluation, the ΔrTTD had the largest AUC (0.873). Eleven features were selected from the TTD parameter to build the delta-radiomics model. The classifiers of the support vector machine and k-nearest neighbors showed good diagnostic performance with AUC values of 0.933 and 0.867, respectively. Conclusion The TTD-based delta-radiomics model has the potential to identify collateral vessel formation after the operation.
Prediction of post-traumatic growth in the face of the COVID-19 crisis based on resilience, post-traumatic stress and social participation: A longitudinal study

The COVID-19 crisis has generated a severe and negative psychological impact worldwide. Despite this, it is also possible to experience post-traumatic growth (PTG). This study aimed to longitudinally explore the prevalence of PTG in the Spanish population and test a predictive model for PTG from resilience, post-traumatic stress symptoms (PTSS), and participation in social activities. Data were collected longitudinally in March, July, and November 2020 via an online survey. About 20% of the sample showed moderate-high levels of PTG, with no significant differences over time. The predictive model explained 19% of the variance in PTG, showing that the inverse relation between resilience and PTG was mediated by PTSS. Additionally, participation in social activities acted as a predictor of PTG. Women, young people, those who had lost their job and people who had experienced COVID-19 symptoms or the loss of a loved one presented higher PTG. Thus, people have experienced positive changes (PTG), but these did not protect them from adverse symptomatology (PTSS).
Leveraging Predictive Pharmacometrics-Based Algorithms to Enhance Perinatal Care—Application to Neonatal Jaundice

The field of medicine is undergoing a fundamental change, transforming towards a modern data-driven patient-oriented approach. This paradigm shift also affects perinatal medicine as predictive algorithms and artificial intelligence are applied to enhance and individualize maternal, neonatal and perinatal care. Here, we introduce a pharmacometrics-based mathematical-statistical computer program (PMX-based algorithm) focusing on hyperbilirubinemia, a medical condition affecting half of all newborns. Independent datasets from two different centers consisting of total serum bilirubin measurements were utilized for model development (342 neonates, 1,478 bilirubin measurements) and validation (1,101 neonates, 3,081 bilirubin measurements), respectively. The mathematical-statistical structure of the PMX-based algorithm is a differential equation in the context of non-linear mixed effects modeling, together with Empirical Bayesian Estimation to predict bilirubin kinetics for a new patient. Several clinically relevant prediction scenarios were validated, i.e., prediction up to 24 h based on one bilirubin measurement, and prediction up to 48 h based on two bilirubin measurements. The PMX-based algorithm can be applied in two different clinical scenarios. First, bilirubin kinetics can be predicted up to 24 h based on one single bilirubin measurement with a median relative (absolute) prediction difference of 8.5% (median absolute prediction difference 17.4 μmol/l), and sensitivity and specificity of 95.7 and 96.3%, respectively. Second, bilirubin kinetics can be predicted up to 48 h based on two bilirubin measurements with a median relative (absolute) prediction difference of 9.2% (median absolute prediction difference 21.5 μmol/l), and sensitivity and specificity of 93.0 and 92.1%, respectively. In contrast to currently available nomogram-based static bilirubin stratification, the PMX-based algorithm presented here is a dynamic approach predicting individual bilirubin kinetics up to 48 h, an intelligent, predictive algorithm that can be incorporated in a clinical decision support tool. Such clinical decision support tools have the potential to benefit perinatal medicine facilitating personalized care of mothers and their born and unborn infants.
S-Ketamine oral thin film—Part 2: Population pharmacodynamics of S-ketamine, S-norketamine and S-hydroxynorketamine

Ketamine is a versatile drug used for many indications and is administered via various routes. Here, we report on the pharmacodynamics of sublingual and buccal fast-dissolving oral-thin-films that contain 50 mg of S-ketamine in a population of healthy male and female volunteers. Twenty volunteers received one or two 50 mg S-ketamine oral thin films in a crossover design, placed for 10 min sublingually (n = 15) or buccally (n = 5). The following measurements were made for 6 h following the film placement: antinociception using three distinct pain assay; electrical, pressure, and heat pain, and drug high on an 11-point visual analog scale. Blood samples were obtained for the measurement of plasma S-ketamine, S-norketamine, and S-hydroxynorketamine concentrations. A population pharmacodynamic analysis was performed in NONMEM to construct a pharmacodynamic model of S-ketamine and its metabolites. P-values < 0.01 were considered significant. The sublingual and buccal 50 and 100 mg S-ketamine oral thin films were antinociceptive and produced drug high with effects lasting 2–6 h, although a clear dose-response relationship for antinociception could not be established. The effects were solely related to the parent compound with no contribution from S-norketamine or S-hydroxynorketamine. S-ketamine potency was lower for antinociception (C50 ranging from 1.2 to 1.7 nmol/mL) than for drug high (C50 0.3 nmol/ml). The onset/offset of effect as defined by the blood-effect-site equilibration half-life did not differ among endpoints and ranged from 0 to 5 min. In conclusion, the 50-mg S-ketamine oral thin film was safe and produced long-term antinociception in all three nociceptive assays with side effects inherent to the use of ketamine. The study was registered at the trial register of the Dutch Cochrane Center (www.trialregister.nl) under identifier NL9267 and the European Union Drug Regulating Authorities Clinical Trials (EudraCT) database under number 2020-005185-33.
The cost-effectiveness of digital health interventions: A systematic review of the literature

Background Digital health interventions have significant potential to improve safety, efficacy, and quality of care, reducing waste in healthcare costs. Despite these premises, the evidence regarding cost and effectiveness of digital tools in health is scarce and limited. Objectives The aim of this systematic review is to summarize the evidence on the cost-effectiveness of digital health interventions and to assess whether the studies meet the established quality criteria. Methods We queried PubMed, Scopus and Web of Science databases for articles in English published from January 1, 2016 to December 31, 2020 that performed economic evaluations of digital health technologies. The methodological rigorousness of studies was assessed with the Consolidated Health Economic Evaluation Reporting Standards (CHEERS). The review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2009 checklist. Results Search identified 1,476 results, 552 of which were selected for abstract and 35 were included in this review. The studies were heterogeneous by country (mostly conducted in upper and upper-middle income countries), type of eHealth intervention, method of implementation, and reporting perspectives. The qualitative analysis identified the economic and effectiveness evaluation of six different types of interventions: (1) seventeen studies on new video-monitoring service systems; (2) five studies on text messaging interventions; (3) five studies on web platforms and digital health portals; (4) two studies on telephone support; (5) three studies on new mobile phone-based systems and applications; and (6) three studies on digital technologies and innovations. Conclusion Findings on cost-effectiveness of digital interventions showed a growing body of evidence and suggested a generally favorable effect in terms of costs and health outcomes. However, due to the heterogeneity across study methods, the comparison between interventions still remains difficult. Further research based on a standardized approach is needed in order to methodically analyze incremental cost-effectiveness ratios, costs, and health benefits.
Bipartite graph search optimization for type II diabetes mellitus Jamu formulation using branch and bound algorithm

Jamu is an Indonesian traditional herbal medicine that has been practiced for generations. Jamu is made from various medicinal plants. Each plant has several compounds directly related to the target protein that are directly associated with a disease. A pharmacological graph can form relationships between plants, compounds, and target proteins. Research related to the prediction of Jamu formulas for some diseases has been carried out, but there are problems in finding combinations or compositions of Jamu formulas because of the increase in search space size. Some studies adopted the drug–target interaction (DTI) implemented using machine learning or deep learning to predict the DTI for discovering the Jamu formula. However, this approach raises important issues, such as imbalanced and high-dimensional dataset, overfitting, and the need for more procedures to trace compounds to their plants. This study proposes an alternative approach by implementing bipartite graph search optimization using the branch and bound algorithm to discover the combination or composition of Jamu formulas by optimizing the search on a plant–protein bipartite graph. The branch and bound technique is implemented using the search strategy of breadth first search (BrFS), Depth First Search, and Best First Search. To show the performance of the proposed method, we compared our method with a complete search algorithm, searching all nodes in the tree without pruning. In this study, we specialize in applying the proposed method to search for the Jamu formula for type II diabetes mellitus (T2DM). The result shows that the bipartite graph search with the branch and bound algorithm reduces computation time up to 40 times faster than the complete search strategy to search for a composition of plants. The binary branching strategy is the best choice, whereas the BrFS strategy is the best option in this research. In addition, the the proposed method can suggest the composition of one to four plants for the T2DM Jamu formula. For a combination of four plants, we obtain Angelica Sinensis, Citrus aurantium, Glycyrrhiza uralensis, and Mangifera indica. This approach is expected to be an alternative way to discover the Jamu formula more accurately.
Contextuality in Quantum Mechanics: Testing the Klyachko Inequality

The Klyachko inequality is an inequality for the probabiities of the values of five observables of a spin-1 particle, which is satisfied by any noncontextual assignment of values to this set of observables, but is violated by the probabilities defined by a certain quantum state. We describe an experiment between two entangled spin-1 particles to test contextuality via a related inequality. We point out that a test of contextuality by measurements on a single particle to confirm the Klyachko inequality requires an assumption of non-disturbance by the measuring instrument, which is avoided in the two-particle experiment.
A nomogram to predict prolonged stay of obesity patients with sepsis in ICU: Relevancy for predictive, personalized, preventive, and participatory healthcare strategies

Objective In an era of increasingly expensive intensive care costs, it is essential to evaluate early whether the length of stay (LOS) in the intensive care unit (ICU) of obesity patients with sepsis will be prolonged. On the one hand, it can reduce costs; on the other hand, it can reduce nosocomial infection. Therefore, this study aimed to verify whether ICU prolonged LOS was significantly associated with poor prognosis poor in obesity patients with sepsis and develop a simple prediction model to personalize the risk of ICU prolonged LOS for obesity patients with sepsis. Method In total, 14,483 patients from the eICU Collaborative Research Database were randomized to the training set (3,606 patients) and validation set (1,600 patients). The potential predictors of ICU prolonged LOS among various factors were identified using logistic regression analysis. For internal and external validation, a nomogram was developed and performed. Results ICU prolonged LOS was defined as the third quartile of ICU LOS or more for all sepsis patients and demonstrated to be significantly associated with the mortality in ICU by logistic regression analysis. When entering the ICU, seven independent risk factors were identified: maximum white blood cell, minimum white blood cell, use of ventilation, Glasgow Coma Scale, minimum albumin, maximum respiratory rate, and minimum red blood cell distribution width. In the internal validation set, the area under the curve was 0.73, while in the external validation set, it was 0.78. The calibration curves showed that this model predicted probability due to actually observed probability. Furthermore, the decision curve analysis and clinical impact curve showed that the nomogram had a high clinical net benefit. Conclusion In obesity patients with sepsis, we created a novel nomogram to predict the risk of ICU prolonged LOS. This prediction model is accurate and reliable, and it can assist patients and clinicians in determining prognosis and making clinical decisions.