Exosomes From IgE-Stimulated Mast Cells Aggravate Asthma-Mediated Atherosclerosis Through circRNA CDR1as-Mediated Endothelial Cell Dysfunction in Mice.

BACKGROUND: IgE has been known for mediating endothelial cell dysfunction and mast cell (MC) activation to fuel asthma-aggravated high-fat diet-induced atherosclerosis. However, it remains unclear for the mechanism of asthma-mediated atherosclerosis, especially the potential involvement of IgE in the exacerbation of asthma-mediated atherosclerosis with a standard laboratory diet, and the cross talk between endothelial cells and MCs. METHODS: Asthma-mediated atherosclerosis mice models under a standard laboratory diet and FcεR1 knock-out mice were used to determine the role of IgE-FcεR1 signaling in asthma-mediated atherosclerosis, which was assessed by Oil Red O staining and immunohistochemistry. Various in vitro assays including nanoparticle tracking analysis and transmission electron microscopy were used to evaluate exosome characteristics. Immunofluorescence and fluorescent in situ hybridization approaches were used to evaluate the effect and mechanism of MC-secreted exosomes encapsulated circular RNA CDR1as (cerebellar degeneration-related 1 antisense) on endothelial cells in vivo and in vitro. Finally, cohort studies examined the plasma CDR1as levels in patients with atherosclerosis with or without allergies. RESULTS: Asthma mice with a standard laboratory diet showed increased atherosclerotic lesions and inflammatory infiltration depending on IgE-FcεR1 signal. FcεR1 knockout mice and blockage of IgE-FcεR1 signaling with IgE monoclonal antibody, omalizumab, all significantly alleviated asthma-mediated atherosclerosis and vascular inflammatory remodeling. Anti-inflammation with dexamethasone and stabilization of MC with cromolyn partially alleviated atherosclerotic lesions and mitigated the inflammatory infiltration in arteries. Mechanistically, IgE stimulation upregulates MC CDR1as expression in exosomes and upregulates the endothelial cell adhesive factors VCAM-1 (vascular cell adhesion molecule-1) and ICAM-1 (intercellular adhesion molecule-1) via the CDR1as-FUS (fused in sarcoma)-phos-p65 axis. Knockdown of CDR1as in vivo significantly decreased the endothelial adhesion function and mitigated asthma-mediated atherosclerosis. Furthermore, a cohort study indicated higher plasma CDR1as levels in patients with atherosclerosis with allergies than in patients with atherosclerosis and healthy controls. CONCLUSIONS: Exosomes from IgE-stimulated MCs aggravated atherosclerosis through circular RNA CDR1as-mediated endothelial dysfunction, providing a novel insight into asthma-mediated atherosclerosis and potential diagnostic and therapeutic targets.

Tailoring planar slip to achieve pure metal-like ductility in body-centred-cubic multi-principal element alloys.

Uniform tensile ductility (UTD) is crucial for the forming/machining capabilities of structural materials. Normally, planar-slip induced narrow deformation bands localize the plastic strains and hence hamper UTD, particularly in body-centred-cubic (bcc) multi-principal element high-entropy alloys (HEAs), which generally exhibit early necking (UTD < 5%). Here we demonstrate a strategy to tailor the planar-slip bands in a Ti-Zr-V-Nb-Al bcc HEA, achieving a 25% UTD together with nearly 50% elongation-to-failure (approaching a ductile elemental metal), while offering gigapascal yield strength. The HEA composition is designed not only to enhance the B2-like local chemical order (LCO), seeding sites to disperse planar slip, but also to generate excess lattice distortion upon deformation-induced LCO destruction, which promotes elastic strains and dislocation debris to cause dynamic hardening. This encourages second-generation planar-slip bands to branch out from first-generation bands, effectively spreading the plastic flow to permeate the sample volume. Moreover, the profuse bands frequently intersect to sustain adequate work-hardening rate (WHR) to large strains. Our strategy showcases the tuning of plastic flow dynamics that turns an otherwise-undesirable deformation mode to our advantage, enabling an unusual synergy of yield strength and UTD for bcc HEAs.

Rapid diagnosis of cervical cancer based on serum FTIR spectroscopy and support vector machines.

Cervical cancer is one of the most common malignant tumors among female gynecological diseases. This paper aims to explore the feasibility of utilizing serum Fourier Transform Infrared (FTIR) spectroscopy, combined with machine learning and deep learning algorithms, to efficiently differentiate between healthy individuals, hysteromyoma patients, and cervical cancer patients. In this study, serum samples from 30 groups of hysteromyoma, 36 groups of cervical cancer, and 30 healthy groups were collected and FTIR spectra of each group were recorded. In addition, the raw datasets were averaged according to the number of scans to obtain an average dataset, and the raw datasets were spectrally enhanced to obtain an augmentation dataset, resulting in a total of three sets of data with sizes of 258, 96, and 1806, respectively. Then, the hyperparameters in the four kernel functions of the Support Vector Machine (SVM) model were optimized by grid search and leave-one-out (LOO) cross-validation. The resulting SVM models achieved recognition accuracies ranging from 85.0% to 100.0% on the test set. Furthermore, a one-dimensional convolutional neural network (1D-CNN) demonstrated a recognition accuracy of 75.0% to 90.0% on the test set. It can be concluded that the use of serum FTIR spectroscopy combined with the SVM algorithm for the diagnosis of cervical cancer has important medical significance.

Deformation Mechanisms and Remarkable Strain Hardening in Single-Crystalline High-Entropy-Alloy Micropillars/Nanopillars.

There have been very limited studies on plastic deformation mechanisms in single-crystalline high-entropy alloys (HEAs) with body-centered cubic (BCC) phases. We performed in situ uniaxial compression on single-crystalline BCC AlCrFeCoNi micropillars/nanopillars with three orientations (including [100], [110], and [111]) and diameters of 270-1583 nm, inside a scanning electron microscope. The experimental results showed the significant size effects on yield/flow stress and the remarkable strain hardening in these HEA micropillars/nanopillars. Especially, HEA micropillars/nanopillars with ⟨100⟩ orientation exhibited higher strain hardening exponents than BCC pure metals and Al0.7CrCoFeNi counterparts. A combination of transmission electron microscopy observations and large-scale atomistic simulations revealed that dislocation slip, reaction, tangling and accumulation, and solid solution effects are responsible for the observed size effects on yield/flow stress and remarkable strain hardening, but these dislocation mechanisms are dependent on nanopillar orientation. Our present study sheds light on the underlying deformation mechanisms in BCC HEA single crystals.

A hybrid adaptive approach for instance transfer learning with dynamic and imbalanced data.

Machine learning has demonstrated success in clinical risk prediction modeling with complex electronic health record data. However, the evolving nature of clinical practices can dynamically change the underlying data distribution over time, leading to model performance drift. Adopting an outdated model is potentially risky and may result in unintentional losses. In this paper, we propose a novel Hybrid Adaptive Boosting approach (HA-Boost) for transfer learning. HA-Boost is characterized by the domain similarity-based and class imbalance-based adaptation mechanisms, which simultaneously address two critical limitations of the classical TrAdaBoost algorithm. We validated HA-Boost in predicting hospital-acquired acute kidney injury using real-world longitudinal electronic health records data. The experiment results demonstrate that HA-Boost stably outperforms the competing baselines in terms of both AUROC and AUPRC across a 7-year time span. This study has confirmed the effectiveness of transfer learning as a superior model updating approach in dynamic environment.

Novel deep learning-based transcriptome data analysis for drug-drug interaction prediction with an application in diabetes.

BACKGROUND: Drug-drug interaction (DDI) is a serious public health issue. The L1000 database of the LINCS project has collected millions of genome-wide expressions induced by 20,000 small molecular compounds on 72 cell lines. Whether this unified and comprehensive transcriptome data resource can be used to build a better DDI prediction model is still unclear. Therefore, we developed and validated a novel deep learning model for predicting DDI using 89,970 known DDIs extracted from the DrugBank database (version 5.1.4). RESULTS: The proposed model consists of a graph convolutional autoencoder network (GCAN) for embedding drug-induced transcriptome data from the L1000 database of the LINCS project; and a long short-term memory (LSTM) for DDI prediction. Comparative evaluation of various machine learning methods demonstrated the superior performance of our proposed model for DDI prediction. Many of our predicted DDIs were revealed in the latest DrugBank database (version 5.1.7). In the case study, we predicted drugs interacting with sulfonylureas to cause hypoglycemia and drugs interacting with metformin to cause lactic acidosis, and showed both to induce effects on the proteins involved in the metabolic mechanism in vivo. CONCLUSIONS: The proposed deep learning model can accelerate the discovery of new DDIs. It can support future clinical research for safer and more effective drug co-prescription.

Midterm Results of Retrograde In Situ Needle Fenestration During Thoracic Endovascular Aortic Repair of Aortic Arch Pathologies.

PURPOSE: To evaluate the safety and feasibility of the in situ needle fenestration (ISNF) technique for reconstruction of the left subclavian artery (LSA) during thoracic endovascular aortic repair (TEVAR) of complicated aortic arch pathologies. MATERIALS AND METHODS: A retrospective review was conducted from January 2014 to December 2019 of 50 patients (mean age 60.2±11.1; 45 men) who underwent ISNF to revascularize the LSA during TEVAR. Twenty-one of the patients also required revascularization of the left common carotid artery (LCCA; n=19) and innominate artery (IA; n=2) using physician-modified in vitro fenestration. Overall, 73 supra-aortic branches were targeted for revascularization. RESULTS: ISNF was successful in 48 patients (96%); one LSA could not be stented and a tortuous LSA prevented the needle from fenestrating the graft. No perioperative major adverse event occurred. There were no type I and 4 type III endoleaks (8%), 3 of which occurred among the first 20 cases. Types II and IV endoleaks were found in 3 (6%) and 6 (12%) cases, respectively; all disappeared during a median follow-up of 15 months (range 3-66). One death (2%) occurred within 12 months due to cerebral hemorrhage. Two patients (4%) required open reinterventions at 6 and 62 months. CONCLUSION: ISNF for revascularization of the LSA during TEVAR seems to be feasible with acceptable midterm outcomes. The learning curve and evolving patient selection criteria affected technical success, complications, and the need for reinterventions. Long-term durability requires further evaluation.

Electrolysis-assisted UV/sulfite oxidation for water treatment with automatic adjustments of solution pH and dissolved oxygen.

Sulfite as precursor to generate sulfate radical (SO4 •-) for water treatment has gained attention. Here we report a metal-free and highly efficient electro/UV/sulfite process to produce SO4 •- for water treatment. UV/sulfite reaction induces sulfite radical (SO3 •-), which transforms into SO4 •- in the presence of oxygen generated by water electrolysis. Electro/UV/sulfite process generates a steady-state SO4 •- concentration of 0.2 to 1.1 × 10-12 M in our tests. Solution pH affects sulfite species distribution, and higher pH mediates improved yield of steady-state SO4 •- concentration. Effect of sulfite concentration exhibits a bell-shaped pattern toward SO4 •- production due to self-scavenging. The oxidation capability of electro/UV/sulfite process is manifested by removing representative micropollutants (i.e., ibuprofen, salicylic acid, and bisphenol A) and Escherichia coli model pathogen, in both synthetic and natural water matrices. This novel electro/UV/sulfite process has obvious advantages, since it bypasses metal ion catalysts, supplies reaction with electrolytically generated nascent oxygen, and overcomes the acidic pH requirement, that are challenging to traditional metal/sulfite processes. Considering the features of environmental friendliness and low cost, the proposed electro/UV/sulfite process should lead to successful applications in the future.

Mechanism of carbon tetrachloride reduction in ferrous ion activated calcium peroxide system in the presence of methanol.

This study investigated the reductive initiation for the depletion of highly oxidized/perhalogenated pollutants, specifically the degradation of carbon tetrachloride (CT) was induced by adding methanol (MeOH) into a ferrous ion (Fe(II)) activated calcium peroxide (CaO2) system. The results indicated that CT could be completely degraded within 20 min at CaO2/Fe(II)/MeOH/CT molar ratio of 30/40/10/1 in this system. Scavenging tests suggested that both superoxide radical anion (O2 •-) and carbon dioxide radical anion (CO2 •-) were predominant reactive species responsible for CT destruction. Hydroxymethyl radicals (•CH2OH), an intermediate in the transformation of MeOH, could also initiate CT degradation by reducing C-Cl bond. GC/MS analysis identified CHCl3, C2Cl4, and C2Cl6 as the intermediates accompanied by CT destruction, and a reduction mechanism for CT degradation was proposed accordingly. In addition, the impact of solution matrix and initial solution pH were evaluated, and the results showed that Cl-, NO3 -, and HCO3 - had adverse effects on CT degradation. Moreover, the alkaline condition was unfavorable to CT depletion. In conclusion, the results obtained in the actual groundwater tests encouragingly demonstrated that the CaO2/Fe(II)/MeOH process is a highly promising technique for the remediation of CT-contaminated groundwater.

Insight into CaO2-based Fenton and Fenton-like systems: strategy for CaO2-based oxidation of organic contaminants.

This study conducted a comparison of the CaO2-based Fenton (CaO2/Fe(II)) and Fenton-like (CaO2/Fe(III)) systems on their benzene degradation performance. The H2O2, Fe(II), Fe(III), and HO● variations were investigated during the benzene degradation. Although benzene has been totally removed in the two systems, the variation patterns of the investigated parameters were different, leading to the different benzene degradation patterns. In terms of the Fe(II)/Fe(III) conversion, the CaO2/Fe(II) and CaO2/Fe(III) systems were actually inseparable and had the inherent mechanism relationships. For the CaO2/Fe(III) system, the initial Fe(III) must be converted to Fe(II), and then the consequent Fenton reaction could be later developed with the regenerated Fe(II). Moreover, some benzene degradation intermediates could have the ability to facilitate the transformation of the Fe(III) to Fe(II) without the classic H2O2-associated propagation reactions. By varying the Fe(II) dosing method, an effective degradation strategy has been developed to take advantage of the two CaO2-based oxidation systems. The proposed strategy was further successfully tested in TCE degradation, therefore extending the potential for the application of this technique.

Electrolytic control of hydrogen peroxide release from calcium peroxide in aqueous solution.

The in situ generation of hydrogen peroxide (H2O2) for water treatment is more practical than the use of liquid H2O2, which is costly to store and transport. Calcium peroxide (CaO2), a solid carrier of H2O2, can release H2O2 on dissolution in water. However, the constant H2O2 release rate of CaO2 has been a bottleneck constraining its wider application. In this study, a practical electrochemical method using a divided cell is developed to control the rate of release of H2O2 from CaO2. The results show that the rate of H2O2 release from CaO2 is enhanced in the anolyte. The increase in H2O2 release is positively correlated with the current. Under a current of 100 mA, the H2O2 concentration was 2.5 times higher after 30 min of electrolysis than in the control experiment in which no current was applied. Water electrolysis in the anodic compartment generates protons that not only: (i) en-hance dissolution of CaO2 and release of H2O2, but also (ii) neutralize the alkaline pH resulting from CaO2 dissolution, thus providing new advantages for the use of CaO2. This effective technique may be suitable for the sophisticated control of H2O2 release in environmental applications.

"Floating" cathode for efficient H2O2 electrogeneration applied to degradation of ibuprofen as a model pollutant.

The performance of the Electro-Fenton (EF) process for contaminant degradation depends on the rate of H2O2 production at the cathode via 2-electron dissolved O2 reduction. However, the low solubility of O2 (≈1×10-3 mol dm-3) limits H2O2 production. Herein, a novel and practical strategy that enables the synergistic utilization of O2 from the bulk electrolyte and ambient air for efficient H2O2 production is proposed. Compared with a conventional "submerged" cathode, the H2O2 concentration obtained using the "floating" cathode is 4.3 and 1.5 times higher using porous graphite felt (GF) and reticulated vitreous carbon (RVC) foam electrodes, respectively. This surprising enhancement results from the formation of a three-phase interface inside the porous cathode, where the O2 from ambient air is also utilized for H2O2 production. The contribution of O2 from ambient air varies depending on the cathode material and is calculated to be 76.7% for the GF cathode and 35.6% for the RVC foam cathode. The effects of pH, current, and mixing on H2O2 production are evaluated. Finally, the EF process enhanced by the "floating" cathode degraded 78.3% of the anti-inflammatory drug ibuprofen after 120 min compared to only 25.4% using a conventional "submerged" electrode, without any increase in the cost.

Insight on the generation of reactive oxygen species in the CaO2/Fe(II) Fenton system and the hydroxyl radical advancing strategy.

Calcium peroxide (CaO2) is a stable hydrogen peroxide (H2O2) carrier, and the CaO2/Fe(II) system has been applied for treatment of various pollutants. It is commonly reported in the literature that hydroxyl radical (HO●) and superoxide radical anions (O2 ●-) are the two main reactive oxygen species (ROSs) generated in the CaO2/Fe(II) system. However, many of the reported results were deduced from degradation performance rather than specific testing of radical generation. Thus, the specific generation of ROSs and the influence of system conditions on ROSs yield is still unclear. To our knowledge, this is the first study specifically focusing on the generation of HO● and O2 ●- in the CaO2/Fe(II) system. Experimental conditions were optimized to investigate the production of HO● and O2 ●-. The results showed the influences of CaO2, Fe(II), and solution pH on HO● and O2 ●- generation, and the HO● generation efficiency was reported for the first time. In addition, the ROSs generation pathways in the CaO2/Fe(II) system were elucidated. A strategy for enhancing HO● yield is developed, based on the continuously dosing Fe(II). This proposed strategy has implications for the effective application of in situ chemical oxidation employing CaO2/Fe(II) for groundwater remediation.

The C-reactive protein/albumin ratio, a validated prognostic score, predicts outcome of surgical renal cell carcinoma patients.

BACKGROUND: The preoperative C-reactive protein/Albumin (CRP/Alb) ratio has been shown to be valuable in predicting the prognosis of patients with certain cancers. The aim of our study is to explore its prognostic value in patients with renal cell carcinoma (RCC). METHODS: A retrospective study was performed in 570 RCC patients underwent radical or partial nephrectomy including 541 patients who received full resection of localized (T1-3 N0/+ M0) RCC. The optimal cutoff value of CRP/Alb was determined by the receive operating characteristic (ROC) analysis. The impact of the CRP/Alb and other clinicopathological characteristics on overall survival (OS) and disease-free survival (DFS) was evaluated using the univariate and multivariate Cox regression analysis. RESULTS: The optimal cutoff of CRP/Alb ratio was set at 0.08 according to the ROC analysis. Multivariate analysis indicated that CRP/Alb ratio was independently associated with OS of RCC patients underwent radical or partial nephrectomy (hazard ratio [HR]: 1.94; 95% confidence interval [95% CI]: 1.12-3.36; P = 0.018), and DFS of localized RCC patients underwent full resection (HR: 2.14; 95% CI: 1.22-3.75; P = 0.008). CONCLUSION: Elevated CRP/Alb ratio was an independent prognostic indicator for poor OS in patients underwent radical or partial nephrectomy and DFS of localized RCC patients underwent full resection. Overall, CRP/Alb may help to identify patients with high relapse risk.

Effects of partial replacement of fish meal by yeast hydrolysate on complement system and stress resistance in juvenile Jian carp (Cyprinus carpio var. Jian).

A 10-week feeding trial was carried out to investigate the effects of dietary fish meal replacement by yeast hydrolysate (YH) on growth performance, complement system and stress resistance of juvenile Jian carp (Cyprinus carpio var. Jian) (initial average weight 19.44 ± 0.06 g). In the study, there were five groups: one control group was fed with a basal diet (YH0), and four treatment groups were fed with dietary fish meal replaced by 1% YH (YH1), 3% (YH3), 5% (YH5) and 7% (YH7), respectively. Each group had four replicates. At the end of feeding trial, twelve fish from each group (three fish per replicate) were randomly selected for assessing the growth and immunity. Meanwhile, 20 fish per replicate were injected by Aeromonas hydrophila. The results showed that (1) Replacement levels of YH significantly affected the growth of the fish with the highest values of weight gain (WG) occurred in fish fed YH3 diet. However, no significant difference in feed conversion ratios (FCR) was observed among all groups. (2) Pre-stressed plasma lysozyme activity, total protein and albumin contents and complement component 3 (C3) and complement component 4 (C4) levels of fish fed YH3 diet were significantly higher than those of fish fed YH0 diet. However, post-stressed immune parameters of fish in all groups were significantly lower. (3) There was a trend that the expression levels of the complement-related genes (c1r/s-A, c4-1, c3-H1, c5-1, fb/c2-A, mbl-2 and masp) initially increased and then decreased except mbl-2 and masp, with the maximum values observed in fish fed YH3 diet. Before stress, the expression levels of the inflammation-related genes (alp, il-1ß and tnf-α) in the hepatopancreas and spleen of fish fed YH1 diet and YH7 diet were significant higher than that of fish fed YH0 diet. After stress, no significant difference in the expression levels of those genes was observed among all groups. These results indicated that FM replacement by YH could improve growth performance, enhance innate immunity, and activate complement via the alternative complement pathway (ACP) and the classical complement pathway (CCP).

Benzene oxidation by Fe(III)-catalyzed sodium percarbonate: matrix constituent effects and degradation pathways.

Complete degradation of benzene by the Fe(III)-activated sodium percarbonate (SPC) system is demonstrated. Removal of benzene at 1.0 mM was seen within 160 min, depending on the molar ratios of SPC to Fe(III). A mechanism of benzene degradation was elaborated by free-radical probe-compound tests, free-radical scavengers tests, electron paramagnetic resonance (EPR) analysis, and determination of Fe(II) and H2O2 concentrations. The degradation products were also identified using gas chromatography-mass spectrometry method. The hydroxyl radical (HO.) was the leading species in charge of benzene degradation. The formation of HO. was strongly dependent on the generation of the organic compound radical (R.) and superoxide anion radical (O.). Benzene degradation products included hydroxylated derivatives of benzene (phenol, hydroquinone, benzoquinone, and catechol) and aliphatic acids (oxalic and fumaric acids). The proposed degradation pathways are consistent with radical formation and identified products. The investigation of selected matrix constituents showed that the Cl and HCO3 had inhibitory effects on benzene degradation. Natural organic matter (NOM) had accelerating influence in degrading benzene. The developed system was tested with groundwater samples and it was found that the Fe(III)-activated SPC has a great potential in effective remediation of benzene-contaminated groundwater while more further studies should be done for its practical application in the future because of the complex subsurface environment.

The destruction of benzene by calcium peroxide activated with Fe(II) in water.

The ability of Fe(II)-activated calcium peroxide (CaO2) to remove benzene is examined with a series of batch experiments. The results showed that benzene concentrations were reduced by 20 to 100% within 30 min. The magnitude of removal was dependent on the CaO2/Fe(II)/Benzene molar ratio, with much greater destruction observed for ratios of 4/4/1 or greater. An empirical equation was developed to quantify the destruction rate dependence on reagent composition. The presence of oxidative hydroxyl radicals (HO•) and reductive radicals (primarily O2•-) was identified by probe compound testing and electron paramagnetic resonance (EPR) tests. The results of the EPR tests indicated that the application of CaO2/Fe(II) enabled the radical intensity to remain steady for a relatively long time. The effect of initial solution pH was also investigated, and CaO2/Fe(II) enabled benzene removal over a wide pH range of 3.0~9.0. The results of radical scavenging tests showed that benzene removal occurred primarily by HO• oxidation in the CaO2/Fe(II) system, although reductive radicals also contributed. The intermediates in benzene destruction were identified to be phenol and biphenyl. The results indicate that Fe(II)-activated CaO2 is a feasible approach for treatment of benzene in contaminated groundwater remediation.

Melittin promotes dexamethasone in the treatment of adjuvant rheumatoid arthritis in rats.

Background: Rheumatoid arthritis (RA) is an erosive-destructive inflammation of the joints, and the chronic, long-term stiffness and deformation induced by RA are some of the symptoms of arthritis that are difficult to treat. Dexamethasone (DEX) and melittin (MLT) are two interesting anti-inflammatory substances, both of which possess anti-inflammatory effects exerted through the suppression of the immune system. The purpose of this study was to explore the role of MLT in the treatment of RA by DEX as well as to clarify the influence of MLT on the efficacy and side effects of DEX. Method: The rats were injected with Complete Freund's Adjuvant (CFA) to induce arthritis, followed by treatment with different doses of DEX and/or MLT. The relevant indexes of paw inflammation were determined, and the appetite, growth status, arthritis status, cytokine levels, and organ coefficient of the rats were evaluated. In addition, the paraffin sections of the joint tissues were prepared to analyze the pathological changes. Result: DEX exhibited side effects, notably hindering feed intake and growth, and inducing immune organ lesions in the rats. MLT significantly reduced the side effects of DEX and promoted its efficacy. DEX in combination with MLT demonstrated a synergistic efficacy in RA treatment, showing advantages in detumescence reduction, pro-inflammatory cytokine inhibition, and joint internal pathological improvement. Conclusion: Thus, MLT promoted the efficacy of DEX in adjuvant RA treatment in rats, offering an approach to reduce the use dosage and side effects of DEX.

Amelioration of melittin on adjuvant-induced rheumatoid arthritis: Integrated transcriptome and metabolome.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease lacking a definitive cure. Although conventional treatments such as dexamethasone and methotrexate are prevalent, their usage is constrained by potential adverse effects. Melittin (MLT) has emerged as a promising natural anti-rheumatic drug; however, studies focusing on the role of MLT in modulating the expression and metabolism of RA-related genes are scarce. METHOD: Arthritis was induced in rats using Complete Freund's Adjuvant (CFA), followed by MLT injections for treatment. Post-treatment, the inflammatory status of each group was assessed, and the mechanistic underpinnings of MLT's ameliorative effects on RA were elucidated through transcriptomic and metabolomic analyses. Additionally, this study conducted qRT-PCR validation of key therapeutic genes and characterized the molecular docking interactions of MLT with key receptor proteins (TNF-α and IL-1ß) using the AutoDock Vina software. RESULT: MLT significantly diminished redness and swelling in affected joints, ameliorated inflammatory cell infiltration, and mitigated joint damage. Integration of transcriptomic and metabolomic data revealed that MLT predominantly regulated the transcription levels of pathways and genes related to cytokines and immune responses, and the metabolic biomarkers of Sphingomyelin, fatty acid, and flavonoid. qRT-PCR confirmed MLT's downregulation of inflammation-related genes such as Il6, Jak2, Stat3, and Ptx3. Molecular docking simulations demonstrated the stable binding of MLT to TNF-α and IL-1ß. CONCLUSION: MLT demonstrated significant efficacy in alleviating RA. This study provides a comprehensive summary of MLT's impact on gene expression and metabolic processes associated with RA.

A Transfer Learning Approach to Correct the Temporal Performance Drift of Clinical Prediction Models: Retrospective Cohort Study.

BACKGROUND: Clinical prediction models suffer from performance drift as the patient population shifts over time. There is a great need for model updating approaches or modeling frameworks that can effectively use the old and new data. OBJECTIVE: Based on the paradigm of transfer learning, we aimed to develop a novel modeling framework that transfers old knowledge to the new environment for prediction tasks, and contributes to performance drift correction. METHODS: The proposed predictive modeling framework maintains a logistic regression-based stacking ensemble of 2 gradient boosting machine (GBM) models representing old and new knowledge learned from old and new data, respectively (referred to as transfer learning gradient boosting machine [TransferGBM]). The ensemble learning procedure can dynamically balance the old and new knowledge. Using 2010-2017 electronic health record data on a retrospective cohort of 141,696 patients, we validated TransferGBM for hospital-acquired acute kidney injury prediction. RESULTS: The baseline models (ie, transported models) that were trained on 2010 and 2011 data showed significant performance drift in the temporal validation with 2012-2017 data. Refitting these models using updated samples resulted in performance gains in nearly all cases. The proposed TransferGBM model succeeded in achieving uniformly better performance than the refitted models. CONCLUSIONS: Under the scenario of population shift, incorporating new knowledge while preserving old knowledge is essential for maintaining stable performance. Transfer learning combined with stacking ensemble learning can help achieve a balance of old and new knowledge in a flexible and adaptive way, even in the case of insufficient new data.