Association of cardiometabolic multimorbidity with all-cause and cardiovascular disease mortality among Chinese hypertensive patients.

BACKGROUND: Hypertension usually clusters with multiple comorbidities. However, the association between cardiometabolic multimorbidity (CMM) and mortality in hypertensive patients is unclear. This study aimed to investigate the association between CMM and all-cause and cardiovascular disease (CVD) mortality in Chinese patients with hypertension. METHODS: The data used in this study were from the China National Survey for Determinants of Detection and Treatment Status of Hypertensive Patients with Multiple Risk Factors (CONSIDER), which comprised 5006 participants aged 19-91 years. CMM was defined as the presence of one or more of the following morbidities: diabetes mellitus, dyslipidemia, chronic kidney disease, coronary heart disease, and stroke. Cox proportional hazard models were used to calculate the hazard ratios (HR) with 95% CI to determine the association between the number of CMMs and both all-cause and CVD mortality. RESULTS: Among 5006 participants [mean age: 58.6 ± 10.4 years, 50% women (2509 participants)], 76.4% of participants had at least one comorbidity. The mortality rate was 4.57, 4.76, 8.48, and 16.04 deaths per 1000 person-years in hypertensive patients without any comorbidity and with one, two, and three or more morbidities, respectively. In the fully adjusted model, hypertensive participants with two cardiometabolic diseases (HR = 1.52, 95% CI: 1.09-2.13) and those with three or more cardiometabolic diseases (HR = 2.44, 95% CI: 1.71-3.48) had a significantly elevated risk of all-cause mortality. The findings were similar for CVD mortality but with a greater increase in risk magnitude. CONCLUSIONS: In this study, three-fourths of hypertensive patients had CMM. Clustering with two or more comorbidities was associated with a significant increase in the risk of all-cause and cardiovascular mortality among hypertensive patients, suggesting more intensive treatment and control in this high-risk patient group.

Roxadustat Versus Erythropoietin: The Comparison of Efficacy in Reversing Ventricular Remodeling in Dialysis Patients with Anaemia.

Background: Renal anaemia and left ventricular hypertrophy are the main complications of chronic kidney disease and are shared among dialysis patients. This retrospective study aimed to compare the efficacies of the hypoxia-inducible factor prolyl hydroxylase inhibitor roxadustat and recombinant human erythropoietin in reversing ventricular remodeling in dialysis patients with renal anaemia. Methods: A total of 204 participants underwent baseline examinations, including echocardiograms and laboratory tests, before being administered either treatment for at least 24 weeks from January 2018 to October 2021, after which follow-up examinations were conducted at 6 months. Propensity score matching based on key variables included age, gender, cardiovascular diseases, cardiovascular medications, dialysis course and the vascular access at baseline was performed to include populations with similar characteristics between groups. Results: In total, 136 patients were included with roxadustat or recombinant human erythropoietin. The left ventricular mass index after treatment with roxadustat and recombinant human erythropoietin both significantly decreased after 6 months, but there was no significant difference in the change in left ventricular mass index between the two groups. In addition, the left ventricular end-diastolic diameters and left ventricular wall thickness, systolic blood pressure, and diastolic blood pressure significantly decreased in the roxadustat group. Roxadustat and recombinant human erythropoietin also increased haemoglobin significantly, but there was no significant difference in the change in haemoglobin between the two groups. The results of multiple linear regression showed that the change in haemoglobin was independent factor affecting the improvement of left ventricular mass index. Conclusions: The increase of haemoglobin was associated with improving left ventricular hypertrophy in dialysis patients. However, the beneficial effects between roxadustat and recombinant human erythropoietin on left ventricular mass index did not show clear superiority or inferiority in six months.

The ratio of neutrophils to lymphocytes effectively predicts clinical outcomes in idiopathic membranous nephropathy.

BACKGROUND: Systemic inflammatory indicators are important in the prognoses of various diseases. Such indicators, including the neutrophil-to-lymphocyte ratio (NLR), can be meaningful in predicting the clinical outcome in patients diagnosed with idiopathic membranous nephropathy (IMN). MATERIALS AND METHODS: 112 IMN patients diagnosed by renal biopsy were recruited retrospectively. The endpoint was defined as a combination of partial and complete remission. Statistical analysis determined the independent factors associated with clinical remission and the predictive utility of NLR. RESULTS: Within the 12-month follow-up period, 72 patients achieved clinical remission after treatment. Univariate analysis identified significant differences in serum albumin, estimated glomerular filtration rate (eGFR), proteinuria, neutrophil count, and NLR between the remission group and the non-remission group (all p < 0.05). Cox proportional hazards indicated that elevated eGFR (HR 1.022, 95% CI (1.009 - 1.035), p = 0.001), lower NLR (HR 0.345, 95% CI (0.237 - 0.501), p = 0.0001), and decreased proteinuria (HR 0.826, 95% CI (0.693 - 0.984), p = 0.032) were protective elements for remission. With an optimal cut-off value of 2.61, the pre-treatment NLR had an excellent ability to identify the remission (area under the curve (AUC), 0.785). Participants were separated into low- and high-NLR groups by using 2.61. Kaplan-Meier survival curves revealed significantly higher remission rates in the lower group (p < 0.0001). CONCLUSION: The NLR is an effective indicator for predicting clinical remission in patients with IMN.

Application of cloud server-based machine learning for assisting pathological structure recognition in IgA nephropathy.

BACKGROUND: Machine learning (ML) models can help assisting diagnosis by rapidly localising and classifying regions of interest (ROIs) within whole slide images (WSIs). Effective ML models for clinical decision support require a substantial dataset of 'real' data, and in reality, it should be robust, user-friendly and universally applicable. METHODS: WSIs of primary IgAN were collected and annotated. The H-AI-L algorithm which could facilitate direct WSI viewing and potential ROI detection for clinicians was built on the cloud server of matpool, a shared internet-based service platform. Model performance was evaluated using F1-score, precision, recall and Matthew's correlation coefficient (MCC). RESULTS: The F1-score of glomerular localisation in WSIs was 0.85 and 0.89 for the initial and pretrained models, respectively, with corresponding recall values of 0.79 and 0.83, and precision scores of 0.92 and 0.97. Dichotomous differentiation between global sclerotic (GS) and other glomeruli revealed F1-scores of 0.70 and 0.91, and MCC values of 0.55 and 0.87, for the initial and pretrained models, respectively. The overall F1-score of multiclassification was 0.81 for the pretrained models. The total glomerular recall rate was 0.96, with F1-scores of 0.68, 0.56 and 0.26 for GS, segmental glomerulosclerosis and crescent (C), respectively. Interstitial fibrosis/tubular atrophy lesion similarity between the true label and model predictions was 0.75. CONCLUSIONS: Our results underscore the efficacy of the ML integration algorithm in segmenting ROIs in IgAN WSIs, and the internet-based model deployment is in favour of widespread adoption and utilisation across multiple centres and increased volumes of WSIs.

Relatively preserved functional immune capacity with standard COVID-19 vaccine regimen in people living with HIV.

Introduction: People living with HIV (PLWH) are at a higher risk of severe disease with SARS-CoV-2 virus infection. COVID-19 vaccines are effective in most PLWH. However, suboptimal immune responses to the standard two-shot regimen are a concern, especially for those with moderate to severe immunodeficiency. An additional dose is recommended as part of the extended primary series in Taiwan. Herein, we study the efficacy of this additional shot in PLWH with mild immunodeficiency compared to that in healthy non-HIV people. Methods: In total, 72 PLWH that were asymptomatic or with mild immunodeficiency (CD4 counts ≥200/mm3) and suppressed virology, and 362 healthcare workers of our hospital were enrolled. None of the participants had a history of SARS-CoV-2 infection. They received mRNA-1273 and ChAdOx1 vaccines. Anti-SARS-CoV-2 neutralizing and anti-Spike IgG antibodies, and SARS-CoV-2-specific T cell responses were evaluated. Results: The standard two-shot regimen elicited lower responses in PLWH than the healthcare workers without HIV infection, although the difference was statistically insignificant. They had comparable levels of neutralizing and anti-Spike antibodies and comparable effector CD4+ and CD8+ T cell responses. The third shot boosted the SARS-CoV-2 immunity significantly more with better antibody responses and higher IFN-γ and IL-2 responses of the CD4+ and CD8+ T cells in PLWH compared to those without HIV. Upon in vitro stimulation with extracted Wuhan strain SARS-CoV-2 proteins, CD8+ T cells from PLWH after 3 shots had more durable effector responses than the non-HIV controls with extended time of stimulation. Conclusion: This subtle difference between PLWH and non-HIV people implied immune exhaustion with two shots in non-HIV people. Slightly compromised immunity in PLWH indeed preserved the functional capacity for further response to the third shot or natural infection.

Nutlin-3 acts as a DNA methyltransferase inhibitor to sensitize esophageal cancer to chemoradiation.

Esophageal squamous cell carcinoma (ESCC) is highly resistant to chemoradiation therapy. We aimed to examine whether Nutlin-3, a molecule that suppresses murine double min 2 (MDM2)-mediated p53 and Retinoblastoma (RB) protein degradation leading to downregulation of DNA methyltransferases (DNMTs), can be a novel therapeutic agent for ESCC. We used wild-type and chemoradiation-resistant ESCC cell lines in this study. The expression of DNMTs, p53 and RB, and methylation level of tumor suppressor genes (TSG) were analyzed upon Nutlin-3 treatment. The antitumor efficacy of Nutlin-3 was investigated in ESCC cell lines and xenograft tumor model. TSG protein expression was checked in the excised tumor tissue. Nutlin-3 induced upregulation of p53 and RB and downregulation of DNMTs proteins in the chemoradiation-resistant and aggressive ESCC cells. The methylation level of TSGs was decreased by Nutlin-3. Nutlin-3 inhibits clonogenic growth of ESCC cells and exerts a synergistic cytotoxic-effect when combined with chemotherapeutic agent cisplatin. Moreover, xenograft tumor growth in SCID mice was suppressed by Nutlin-3. The protein expression level of DNMTs was downregulated, and that of TSGs was upregulated by Nutlin-3 treatment in the excised tumor tissue. In conclusion, Nutlin-3 is a potential therapeutic agent that can potentiate the treatment efficacy of chemoradiation-resistant ESCC.

[Advances in Mechanisms of Blood Brain Barrier Impairment Induced by Sleep Deprivation].

Sleep deprivation,the process and state of partial or complete lack of normal sleep caused by various factors,is prevalent at present.Seriously impairing the physical and mental health,sleep deprivation has become a public health problem that cannot be ignored.Studies have demonstrated that blood-brain barrier impairment is the key pathophysiological process of a variety of neurological diseases.Although clinical and basic studies have suggested that sleep deprivation can induce blood-brain barrier impairment,the underlying mechanisms remain to be elucidated.This review summarizes the advances in the mechanisms of blood-brain barrier impairment induced by sleep deprivation.

Using a machine learning model to predict the development of acute kidney injury in patients with heart failure.

Background: Heart failure (HF) is a life-threatening complication of cardiovascular disease. HF patients are more likely to progress to acute kidney injury (AKI) with a poor prognosis. However, it is difficult for doctors to distinguish which patients will develop AKI accurately. This study aimed to construct a machine learning (ML) model to predict AKI occurrence in HF patients. Materials and methods: The data of HF patients from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database was retrospectively analyzed. A ML model was established to predict AKI development using decision tree, random forest (RF), support vector machine (SVM), K-nearest neighbor (KNN), and logistic regression (LR) algorithms. Thirty-nine demographic, clinical, and treatment features were used for model establishment. Accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUROC) were used to evaluate the performance of the ML algorithms. Results: A total of 2,678 HF patients were engaged in this study, of whom 919 developed AKI. Among 5 ML algorithms, the RF algorithm exhibited the highest performance with the AUROC of 0.96. In addition, the Gini index showed that the sequential organ function assessment (SOFA) score, partial pressure of oxygen (PaO2), and estimated glomerular filtration rate (eGFR) were highly relevant to AKI development. Finally, to facilitate clinical application, a simple model was constructed using the 10 features screened by the Gini index. The RF algorithm also exhibited the highest performance with the AUROC of 0.95. Conclusion: Using the ML model could accurately predict the development of AKI in HF patients.

Basolateral Amygdala Reactive Microglia May Contribute to Synaptic Impairment and Depressive-Like Behavior in Mice with Bone Cancer Pain.

Anxiety and depression induced by cancer-related pain disturb quality of life and willingness to survive. As a component of the limbic system, the basolateral amygdala (BLA) is critical for processing negative emotions. The reactive microglial engulfment of synapses may promote depression during adolescence. However, whether microglia phagocytose synapses to mediate cancer pain-induced depression remains unclear. The present study established a bone cancer-pain model to investigate the association between dendritic spine synapses and depressive-like behavior and explore the phagocytic function of microglia in the BLA. We found that tumor-bearing mice experienced postoperative pain-related depression, and their BLAs exhibited reactive microglia, as well as phagocytic synapses. The microglial inhibitor minocycline effectively mitigated depressive behavior, synaptic damage, and the phagocytic function of microglia. Our study implicates microglia-mediated synaptic loss in the BLA may act as the pathological basis of depressive-like behavior in bone cancer pain model.

Role of Pneumococcal NanC in the Severe Disease of Streptococcus pneumoniae Superinfection with Influenza.

Bacterial superinfection aggravates the disease of influenza. Streptococcus pneumoniae is the most common bacterial pathogen. Synergistic virulence has been demonstrated between influenza neuraminidase and pneumococcal NanA and NanB. NanC, the other pneumococcal neuraminidase infrequently present in clinical isolates, is not well characterized. In this study, we report that superinfection with a NanC-negative pneumococcus strain suppresses anti-influenza immunity and impairs viral clearance with higher TGF-ß activation in mice. Bacterial load in the lungs also increases as the host immunity is suppressed. NanC-positive isogenic mutant reverses wild type S. pneumoniae-mediated immune suppression and facilitates virus clearance. However, it causes more severe disease as the augmented inflammation causes collateral damage. Both virus-mediated damage and immune response-mediated inflammation are important for pathogenesis of severe influenza. Inflammation may be more critical than virus-mediated damage in influenza with bacterial superinfection.

Role of receptor tyrosine kinases mediated signal transduction pathways in tumor growth and angiogenesis-New insight and futuristic vision.

In the past two decades, significant progress has been made in the past two decades towards the understanding of the basic mechanisms underlying cancer growth and angiogenesis. In this context, receptor tyrosine kinases (RTKs) play a pivotal role in cell proliferation, differentiation, growth, motility, invasion, and angiogenesis, all of which contribute to tumor growth and progression. Mutations in RTKs lead to abnormal signal transductions in several pathways such as Ras-Raf, MEK-MAPK, PI3K-AKT and mTOR pathways, affecting a wide range of biological functions including cell proliferation, survival, migration and vascular permeability. Increasing evidence demonstrates that multiple kinases are involved in angiogenesis including RTKs such as vascular endothelial growth factor, platelet derived growth factor, epidermal growth factor, insulin-like growth factor-1, macrophage colony-stimulating factor, nerve growth factor, fibroblast growth factor, Hepatocyte Growth factor, Tie 1 & 2, Tek, Flt-3, Flt-4 and Eph receptors. Overactivation of RTKs and its downstream regulation is implicated in tumor initiation and angiogenesis, representing one of the hallmarks of cancer. This review discusses the role of RTKs, PI3K, and mTOR, their involvement, and their implication in pro-oncogenic cellular processes and angiogenesis with effective approaches and newly approved drugs to inhibit their unrestrained action.

Using Machine Learning to Evaluate the Role of Microinflammation in Cardiovascular Events in Patients With Chronic Kidney Disease.

Background: Lipid metabolism disorder, as one major complication in patients with chronic kidney disease (CKD), is tied to an increased risk for cardiovascular disease (CVD). Traditional lipid-lowering statins have been found to have limited benefit for the final CVD outcome of CKD patients. Therefore, the purpose of this study was to investigate the effect of microinflammation on CVD in statin-treated CKD patients. Methods: We retrospectively analysed statin-treated CKD patients from January 2013 to September 2020. Machine learning algorithms were employed to develop models of low-density lipoprotein (LDL) levels and CVD indices. A fivefold cross-validation method was employed against the problem of overfitting. The accuracy and area under the receiver operating characteristic (ROC) curve (AUC) were acquired for evaluation. The Gini impurity index of the predictors for the random forest (RF) model was ranked to perform an analysis of importance. Results: The RF algorithm performed best for both the LDL and CVD models, with accuracies of 82.27% and 74.15%, respectively, and is therefore the most suitable method for clinical data processing. The Gini impurity ranking of the LDL model revealed that hypersensitive C-reactive protein (hs-CRP) was highly relevant, whereas statin use and sex had the least important effects on the outcomes of both the LDL and CVD models. hs-CRP was the strongest predictor of CVD events. Conclusion: Microinflammation is closely associated with potential CVD events in CKD patients, suggesting that therapeutic strategies against microinflammation should be implemented to prevent CVD events in CKD patients treated by statin.

Integrated analysis of phosphoproteome and ubiquitylome in epididymal sperm of buffalo (Bubalus bubalis).

In mammals, sperm need to mature in the epididymis to gain fertilization competency. However, the molecular mechanism underlying buffalo sperm maturation remains elusive. Exploring sperm physiology at the posttranslational modification (PTM) level could help to develop our understanding of these mechanisms. Protein phosphorylation and ubiquitination are major PTMs in the regulation of many biological processes. In the present study, to our knowledge, we report the first phosphoproteome and ubiquitylome of sperm collected from the caput, corpus, and cauda segments of the epididymis using liquid chromatography-mass spectrometry combined with affinity purification. In total, 647 phosphorylation sites in 294 proteins and 1063 ubiquitination sites in 446 proteins were characterized. Some of these proteins were associated with cellular developmental processes and energy metabolic pathways. Interestingly, 84 proteins were both phosphorylated and ubiquitinated, simultaneously. Some of these proteins were involved in, for example, spermatogenesis, reproduction, and spermatid development. Taken together, these data provide a theoretical basis for further functional analysis of phosphorylation and ubiquitination in epididymal sperm of buffalo and other mammals, and serve as an important resource for exploring the physiological mechanism underlying sperm maturation.

Novel targets identified by integrated proteomic and phosphoproteomic analysis in spermatogenesis of swamp buffalo (Bubalus bubalis).

To understand mechanisms of spermatogenesis, the proteome and the phosphoproteome in prepubertal and pubertal swamp buffalo (Bubalus bubalis) testes were analyzed using tandem mass tag (TMT) coupled with liquid chromatography-tandem mass spectrometry (LC-MS/MS). In prepubertal testes, 80 proteins were overexpressed, 148 proteins were underexpressed, and 139 and 142 protein sites had higher and lower phosphorylation, respectively, compared to the levels in pubertal testes. Several of these proteins were associated with reproductive processes such as sexual reproduction, spermatogenesis, fertilization, and spermatid development. In particular, outer dense fiber protein 1 (ODF1), protein maelstrom homolog (MAEL), actin-like protein 7B (ACTL7B), tyrosine-(Y)-phosphorylation regulated (CABYR), and tripartite motif containing 36 (TRIM36) were upregulated with age at both the proteome and phosphoproteome levels. Combining proteome and phosphoproteome analysis can be effectively applied to study the protein/phosphorylation patterns of buffalo testes. These data provide new regulatory candidates and evidence for a complex network in spermatogenesis in buffalo testes, and serve as an important resource for exploring the physiological mechanism of spermatogenesis in mammals.

Ubiquitome analysis reveals the involvement of lysine ubiquitination in the spermatogenesis process of adult buffalo (Bubalus bubalis) testis.

Protein ubiquitination, a major and conserved post-translational modification, is known to play a critical regulatory role in many biological processes in eukaryotes. Although several ubiquitinated proteins have been found in buffalo (Bubalus bubalis) testis in our previous studies, large-scale profiling of buffalo testis ubiquitome has not been reported to date. In the present study, we first identified a global profiling of lysine ubiquitination of adult buffalo testis using a highly sensitive LC-MS/MS coupled with immune-affinity enrichment of ubiquitinated peptides. In total, 422 lysine ubiquitination sites were identified in 262 proteins in adult buffalo testis tissue. Bioinformatics analysis showed that the ubiquitinated proteins are involved in a variety of biological processes and diverse subcellular localizations. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein interaction network analysis indicated that proteasome, glycolysis/gluconeogenesis and gap junction pathways are modulated by protein ubiquitination in testis. Besides, 44 ubiquitinated proteins may involve in spermatogenesis according to the SpermatogenesisOnline database, of which, the ubiquitination of HSPA2 and UCHL1 were confirmed by Immunoprecipitation (IP)/Western blot analysis. Taken together, these data provide a global view of ubiquitome in buffalo testis for the first time, and serve as an important resource for exploring the physiological role especially spermatogenesis of lysine ubiquitination in testis in mammals.

Solvent-Free One-Shot Synthesis of Thermoplastic Polyurethane Based on Bio-Poly(1,3-propylene succinate) Glycol with Temperature-Sensitive Shape Memory Behavior.

In this work, a new family of fully biobased thermoplastic polyurethanes (TPUs) with thermo-induced shape memory is developed. First, a series of TPUs were successfully synthesized by the one-shot solvent-free bulk polymerization of bio-poly(1,3-propylene succinate) glycol (PPS) with various molecular weights (M n = 1000, 2000, 3000, and 4000), 1,4-butanediol (BDO), and 4,4'-methylene diphenyl diisocyanate (MDI). These polyurethanes (PUs) are denoted as PPS-x-TPUs (x = 1000, 2000, 3000, and 4000), where x represents the M n of PPS in the polymers. To determine the effect of the molecular weight of the soft segment of PU, all PPS-TPUs were formed with the same hard segment content (32.5 wt %). The soft segment with high molecular weight in PPS-4000-TPU caused a high degree of soft segment entanglement and formed many secondary bonds. PPS-4000-TPU exhibited better mechanical (tensile strength: 64.13 MPa and hardness: 90A) and thermomechanical properties (maximum loading: 2.95 MPa and maximum strain: 144%) than PPS-1000-TPU. At an appropriate shape memory programming temperature, all synthesized PPS-x-TPUs exhibited excellent shape memory behaviors with a fixed shape rate of >99% and a shape recovery rate of >86% in the first round and 95% in the following rounds. Therefore, these bio-TPUs with shape memory have potential for use in smart fabrics.

EMULSION: Transparent and flexible multiscale stochastic models in human, animal and plant epidemiology.

Stochastic mechanistic epidemiological models largely contribute to better understand pathogen emergence and spread, and assess control strategies at various scales (from within-host to transnational scale). However, developing realistic models which involve multi-disciplinary knowledge integration faces three major challenges in predictive epidemiology: lack of readability once translated into simulation code, low reproducibility and reusability, and long development time compared to outbreak time scale. We introduce here EMULSION, an artificial intelligence-based software intended to address those issues and help modellers focus on model design rather than programming. EMULSION defines a domain-specific language to make all components of an epidemiological model (structure, processes, parameters…) explicit as a structured text file. This file is readable by scientists from other fields (epidemiologists, biologists, economists), who can contribute to validate or revise assumptions at any stage of model development. It is then automatically processed by EMULSION generic simulation engine, preventing any discrepancy between model description and implementation. The modelling language and simulation architecture both rely on the combination of advanced artificial intelligence methods (knowledge representation and multi-level agent-based simulation), allowing several modelling paradigms (from compartment- to individual-based models) at several scales (up to metapopulation). The flexibility of EMULSION and its capability to support iterative modelling are illustrated here through examples of progressive complexity, including late revisions of core model assumptions. EMULSION is also currently used to model the spread of several diseases in real pathosystems. EMULSION provides a command-line tool for checking models, producing model diagrams, running simulations, and plotting outputs. Written in Python 3, EMULSION runs on Linux, MacOS, and Windows. It is released under Apache-2.0 license. A comprehensive documentation with installation instructions, a tutorial and many examples are available from: https://sourcesup.renater.fr/www/emulsion-public.

Effect of aloin on viral neuraminidase and hemagglutinin-specific T cell immunity in acute influenza.

BACKGROUND: Millions of people are infected by the influenza virus worldwide every year. Current selections of anti-influenza agents are limited and their effectiveness and drug resistance are still of concern. PURPOSE: Investigation on in vitro and in vivo effect of aloin from Aloe vera leaves against influenza virus infection. METHODS: In vitro antiviral property of aloin was measured by plaque reduction assay in which MDCK cells were infected with oseltamivir-sensitive A(H1N1)pdm09, oseltamivir-resistant A(H1N1)pdm09, H1N1 or H3N2 influenza A or with influenza B viruses in the presence of aloin. In vivo activity was tested in H1N1 influenza virus infected mice. Aloin-mediated inhibition of influenza neuraminidase activity was tested by MUNANA assay. Aloin treatment-mediated modulation of anti-influenza immunity was tested by the study of hemagglutinin-specific T cells in vivo. RESULTS: Aloin significantly reduced in vitro infection by all the tested strains of influenza viruses, including oseltamivir-resistant A(H1N1)pdm09 influenza viruses, with an average IC50 value 91.83 ± 18.97 µM. In H1N1 influenza virus infected mice, aloin treatment (intraperitoneal, once daily for 5 days) reduced virus load in the lungs and attenuated body weight loss and mortality. Adjuvant aloin treatment also improved the outcome with delayed oseltamivir treatment. Aloin inhibited viral neuraminidase and impeded neuraminidase-mediated TGF-ß activation. Viral neuraminidase mediated immune suppression with TGF-ß was constrained and influenza hemagglutinin-specific T cell immunity was increased. There was more infiltration of hemagglutinin-specific CD4+ and CD8+ T cells in the lungs and their production of effector cytokines IFN-γ and TNF-α was boosted. CONCLUSION: Aloin from Aloe vera leaves is a potent anti-influenza compound that inhibits viral neuraminidase activity, even of the oseltamivir-resistant influenza virus. With suppression of this virus machinery, aloin boosts host immunity with augmented hemagglutinin-specific T cell response to the infection. In addition, in the context of compromised benefit with delayed oseltamivir treatment, adjuvant aloin treatment ameliorates the disease and improves survival. Taken together, aloin has the potential to be further evaluated for clinical applications in human influenza.

Development of amphiphile 4-armed PEO-based Ti4+ complex for highly selective enrichment of phosphopeptides.

Protein phosphorylation is a reversible and important post-translational modification. Identification of phosphopeptides without enrichment is difficult for the low-abundance of phosphopeptides in real complex biological samples. Therefore, the effective and selective concentration of phosphopeptides prior to proteomic identification by mass spectrometer is necessary. In this study, we synthesized a novel titanium-based immobilized metal ion affinity chromatography material for highly selective enrichment of phosphopeptides. To improve material hydrophilia to the maximum extent, titanium ions were immobilized on the 4-armed Poly(ethylene oxide)(4µ-PEO-Ti4+), a totally soluble polymer with large molecular weight (20000 g/mol). The 4µ-PEO-Ti4+ was used to enrich phosphopeptides from tryptic digests of standard proteins and real complex biological samples, followed by MALDI-TOF MS analysis. In enrichment of phosphopeptides from 4 pmol ß-casein, the 4µ-PEO-Ti4+ performed the best property with starting material of 99-132 µg, loading buffer of 50% ACN/5% TFA (v/v), elution buffer of 10% NH3·H2O (v/v) and elution time of 30 min. The 4µ-PEO-Ti4+ has a superior detection sensitivity as low as 2 fmol for phosphopeptides. The high selectivity of 4µ-PEO-Ti4+ allows a deep enrichment of phosphopeptides of ß-casein from a mixture with BSA of 1000-fold abundant. The 4µ-PEO-Ti4+ shows great stability and endurability and can be recycled up to at least 5 times. In addition, 4µ-PEO-Ti4+ could detect 10 and 15 phosphopeptides from non-fat milk and nonenzymatic human saliva, respectively. In total, 4µ-PEO-Ti4+ is a novel excellent material which shows great sensitive and selective enrichment of low-abundance phosphopeptides in real complex biological samples.