Near full-length genome analysis of HEV 4b subtype in pigs showed a similarity up to 99.944% compared to a patient in Guangdong province, China.

Hepatitis E virus (HEV) is a prevalent pathogen responsible for acute viral hepatitis, HEV genotypes 3 and 4 infections causing zoonotic infections. Currently, the nucleotide similarity analysis between humans and pigs for HEV genotype 4 is limited. In this study, stool samples from an HEV-infected patient who is a pig farmer and from pigs were collected to obtain the near full-length genome of HEV, phylogenetic trees were constructed for genotyping, and similarity of HEV sequences was analyzed. The results showed that HEV-RNA was detected in the stool samples from the patient and six pigs (6/30, 20.0%). Both HEV subtype in the patient and pigs was 4b. Additionally, similarity analysis showed that the range was 99.875%-99.944% between the patient and pigs at the nucleotide level. Four isolates of amino acid sequences (ORFs 1-3) from pigs were 100% identical to the patient. Phylogenetic tree and similarity analysis of an additional nine HEV sequences isolated from other patients in this region showed that the HEV sequence from the pig farmer had the closest relationship with the pigs from his farm rather than other sources of infection in this region. This study provides indirect evidences for HEV subtype 4b can be transmitted from pigs to humans at the nucleotide level. Further research is needed to explore the characteristics of different HEV subtypes.

In silico prediction of ocular toxicity of compounds using explainable machine learning and deep learning approaches.

The accurate identification of chemicals with ocular toxicity is of paramount importance in health hazard assessment. In contemporary chemical toxicology, there is a growing emphasis on refining, reducing, and replacing animal testing in safety evaluations. Therefore, the development of robust computational tools is crucial for regulatory applications. The performance of predictive models is heavily reliant on the quality and quantity of data. In this investigation, we amalgamated the most extensive dataset (4901 compounds) sourced from governmental GHS-compliant databases and literature to develop binary classification models of chemical ocular toxicity. We employed 12 molecular representations in conjunction with six machine learning algorithms and two deep learning algorithms to create a series of binary classification models. The findings indicated that the deep learning method GCN outperformed the machine learning models in cross-validation, achieving an impressive AUC of 0.915. However, the top-performing machine learning model (RF-Descriptor) demonstrated excellent performance with an AUC of 0.869 on the test set and was therefore selected as the best model. To enhance model interpretability, we conducted the SHAP method and attention weights analysis. The two approaches offered visual depictions of the relevance of key descriptors and substructures in predicting ocular toxicity of chemicals. Thus, we successfully struck a delicate balance between data quality and model interpretability, rendering our model valuable for predicting and comprehending potential ocular-toxic compounds in the early stages of drug discovery.

AdipoAI suppresses osteoclastogenesis by activating AdipoR1/APPL1: An in vivo experimental study in diabetes-associated peri-implantitis.

AIM: Diabetics experience severe peri-implant inflammatory bone damage. We aimed to provide powerful evidence supporting the novel adiponectin receptor agonist AdipoAI in treating diabetes-associated peri-implantitis. MATERIALS AND METHODS: Twenty-four ZDF-Leprfa/Crl rats were randomly allocated to three groups (N = 8). After feeding with a high-fat diet to establish diabetic rats, experimental peri-implantitis was induced by implanting titanium rods (1.5 mm diameter and 20 mm length) contaminated with Staphylococcus aureus into the femurs. Radiographic evaluation, microCT, histological analyses and qRT-PCR were used to detect inflammatory infiltration and bone destruction. In vitro, the inhibition by AdipoAI of osteoclastogenesis, including the number and function of osteoclasts, was investigated by TRAP staining, immunofluorescence, qRT-PCR and Western blotting. Immunofluorescence, qRT-PCR and Western blotting were also utilized to explore AdipoR1, APPL1, NF-κB and Wnt5a-Ror2 signalling molecules in this process. One-way ANOVA with Tukey's post hoc test was used to compare the data. RESULTS: AdipoAI reduced inflammation and bone destruction caused by peri-implantitis in diabetic rats, which were manifested by a reduction in F4/80-positive macrophage infiltration by 72%, the number of osteoclasts by 58% and the levels of cytokines (p < .05) in disease group. In vitro, 1 µM AdipoAI decreased the number of osteoclasts to 51%, inhibited F-actin ring formation and reduced the levels of related markers (p < .05). Mechanistically, AdipoAI activated AdipoR1/APPL1 and conversely suppressed the phosphorylation of IκB-α, nuclear translocation of P65 and the Wnt5a-Ror2 signalling pathway (p < .05). CONCLUSIONS: AdipoAI suppressed osteoclastogenesis in diabetes-associated peri-implantitis by inhibiting the NF-κB and Wnt5a-Ror2 pathways via the AdipoR1/APPL1 axis.

In silico prediction of hERG blockers using machine learning and deep learning approaches.

The human ether-à-go-go-related gene (hERG) is associated with drug cardiotoxicity. If the hERG channel is blocked, it will lead to prolonged QT interval and cause sudden death in severe cases. Therefore, it is important to evaluate the hERG-blocking property of compounds in early drug discovery. In this study, a dataset containing 4556 compounds with IC50 values determined by patch clamp techniques on mammalian lineage cells was collected, and hERG blockers and non-blockers were distinguished according to three single thresholds and two binary thresholds. Four machine learning (ML) algorithms combining four molecular fingerprints and molecular descriptors as well as graph convolutional neural networks (GCNs) were used to construct a series of binary classification models. The results showed that the best models varied for different thresholds. The ML models implemented by support vector machine and random forest performed well based on Morgan fingerprints and molecular descriptors, with AUCs ranging from 0.884 to 0.950. GCN showed superior prediction performance with AUCs above 0.952, which might be related to its direct extraction of molecular features from the original input. Meanwhile, the classification of binary threshold was better than that of single threshold, which could provide us with a more accurate prediction of hERG blockers. At last, the applicability domain for the model was defined, and seven structural alerts that might generate hERG blockage were identified by information gain and substructure frequency analysis. Our work would be beneficial for identifying hERG blockers in chemicals.

Epo receptor signaling in macrophages alters the splenic niche to promote erythroid differentiation.

Anemic stress induces stress erythropoiesis, which rapidly generates new erythrocytes to restore tissue oxygenation. Stress erythropoiesis is best understood in mice where it is extramedullary and occurs primarily in the spleen. However, both human and mouse stress erythropoiesis use signals and progenitor cells that are distinct from steady-state erythropoiesis. Immature stress erythroid progenitors (SEPs) are derived from short-term hematopoietic stem cells. Although the SEPs are capable of self-renewal, they are erythroid restricted. Inflammation and anemic stress induce the rapid proliferation of SEPs, but they do not differentiate until serum erythropoietin (Epo) levels increase. Here we show that rather than directly regulating SEPs, Epo promotes this transition from proliferation to differentiation by acting on macrophages in the splenic niche. During the proliferative stage, macrophages produce canonical Wnt ligands that promote proliferation and inhibit differentiation. Epo/Stat5-dependent signaling induces the production of bioactive lipid mediators in macrophages. Increased production of prostaglandin J2 (PGJ2) activates peroxisome proliferator-activated receptor γ (PPARγ)-dependent repression of Wnt expression, whereas increased production of prostaglandin E2 (PGE2) promotes the differentiation of SEPs.

Alterations of the human gut microbiome in liver cirrhosis.

Liver cirrhosis occurs as a consequence of many chronic liver diseases that are prevalent worldwide. Here we characterize the gut microbiome in liver cirrhosis by comparing 98 patients and 83 healthy control individuals. We build a reference gene set for the cohort containing 2.69 million genes, 36.1% of which are novel. Quantitative metagenomics reveals 75,245 genes that differ in abundance between the patients and healthy individuals (false discovery rate < 0.0001) and can be grouped into 66 clusters representing cognate bacterial species; 28 are enriched in patients and 38 in control individuals. Most (54%) of the patient-enriched, taxonomically assigned species are of buccal origin, suggesting an invasion of the gut from the mouth in liver cirrhosis. Biomarkers specific to liver cirrhosis at gene and function levels are revealed by a comparison with those for type 2 diabetes and inflammatory bowel disease. On the basis of only 15 biomarkers, a highly accurate patient discrimination index is created and validated on an independent cohort. Thus microbiota-targeted biomarkers may be a powerful tool for diagnosis of different diseases.

Facile Fluorescence Dopamine Detection Strategy Based on Acid Phosphatase (ACP) Enzymatic Oxidation Dopamine to Polydopamine.

Facile and effective detection of dopamine (DA) plays a significant role in current clinical applications. Substantially, special optical nanomaterials are important for fabricating easy-to-control, cheap, selective, and portable fluorescence DA sensors with superior performance. Herein, carbon dots (CDs) prepared from melting method were applied as signal to establish a simple but effective fluorescence strategy for DA determination based on the enzymatic activity of acid phosphatase (ACP), which induces DA to form polydopamine (pDA). The formed pDA caused by the enzymatic oxidization of ACP toward DA can interact with CDs through the inner filter effect. Such behavior effectively quenched the CDs' fluorescence. The degree of fluorescence quenching of CDs was positively correlated with the DA content. Under the optimized reaction conditions, the proposed fluorescence method exhibited a comparable analytical performance with other DA sensors with good selectivity. Furthermore, this method has been successfully applied to detect DA in DA hydrochloride injection and human serum samples. It shows that this method features potential practical application value and is expected to be used in clinical research.

In vitro culture of stress erythroid progenitors identifies distinct progenitor populations and analogous human progenitors.

Tissue hypoxia induces a systemic response designed to increase oxygen delivery to tissues. One component of this response is increased erythropoiesis. Steady-state erythropoiesis is primarily homeostatic, producing new erythrocytes to replace old erythrocytes removed from circulation by the spleen. In response to anemia, the situation is different. New erythrocytes must be rapidly made to increase hemoglobin levels. At these times, stress erythropoiesis predominates. Stress erythropoiesis is best characterized in the mouse, where it is extramedullary and utilizes progenitors and signals that are distinct from steady-state erythropoiesis. In this report, we use an in vitro culture system that recapitulates the in vivo development of stress erythroid progenitors. We identify cell-surface markers that delineate a series of stress erythroid progenitors with increasing maturity. In addition, we use this in vitro culture system to expand human stress erythroid progenitor cells that express analogous cell-surface markers. Consistent with previous suggestions that human stress erythropoiesis is similar to fetal erythropoiesis, we demonstrate that human stress erythroid progenitors express fetal hemoglobin upon differentiation. These data demonstrate that similar to murine bone marrow, human bone marrow contains cells that can generate BMP4-dependent stress erythroid burst-forming units when cultured under stress erythropoiesis conditions.

One-pot hydrothermal synthesis of silicon, nitrogen co-doped carbon dots for enhancing enzyme activity of acid phosphatase (ACP) to dopamine and for cell imaging.

Developing water-soluble nanomaterials with high photoluminescence emission and high yield for biological analysis and imaging is urgently needed. Herein, water-soluble blue emitting silicon and nitrogen co-doped carbon dots (abbreviated as Si-CDs) of a high photoluminescence quantum yield of 80 % were effectively prepared with high yield rate (59.1 %) via one-step hydrothermal treatment of N-[3-(trimethoxysilyl)propyl]ethylenediamine (DAMO) and trans-aconitic acid. Furthermore, the Si-CDs demonstrate environmental robustness, photo-stability and biocompatibility. Given the importance of the potentially abnormal levels of acid phosphatase (ACP) in cancer diagnosis, developing a reliable and sensitive ACP measurement method is of significance for clinical research. The Si-CDs unexpectedly promote the catalytic oxidation of ACP on dopamine (DA) to polydopamine under acidic conditions through the produced reactive oxygen species (ROS). Correspondingly, a fluorescence response strategy using Si-CDs as the dual functions of probes and promoting enzyme activity of ACP on catalyzing DA was constructed to sensitively determine ACP. The quantitative analysis of ACP displayed a linear range of 0.1-60 U/L with a detection limit of 0.056 U/L. The accurate detection of ACP was successfully achieved in human serum through recovery tests. As a satisfactory fluorescent probe, Si-CDs were successfully applied to fluorescent imaging of A549 cells in cytoplasmic with long-term and safe staining. The Si-CDs have the dual properties of outstanding fluorescent probes and auxiliary oxidase activity, indicating their great potential in multifunctional applications.

Sunshine duration and solar radiation contributed to severe Bell's palsy: An 11-year time series analysis based on a distributed lag non-linear model model.

Although previous studies have suggested that meteorological factors are associated with Bell's palsy, articles on this topic are rare and the results are inconsistent. We aim to reveal the relationship between exposure to different meteorological factors and the onset of severe Bell's palsy (SBP) with daily data. A case-crossover study based on time-series data was applied, and the minimum risk value of each climatic factor was set as the reference value. We fitted a distributed lag non-linear model (DLNM) which applied quasi-Poisson regression to evaluate the exposure-response association and the lag-response association of meteorological factors on the occurrence of SBP. The mode value and per-decile interval value of each meteorological factor were all included in the analysis. Sensitivity analyses were conducted to test the robustness of results. A total of 863 SBP patients (474 males and 389 females) from 7 hospitals in the Shenzhen Futian District were selected from January 2009 to February 2020. The highest relations effect was tested in the cumulative exposure-response result shown as follows; mean temperature at the minimum value 15.3°C with RR of 10.370 (1.557-69.077) over lag 0 to 13; relative humidity at the 30th value 71% with RR of 8.041 (1.016-63.616) over lag 0 to 14; wind speed at the 90th value 31 (0.1 m/s) with RR of 1.286 (1.038-1.593) over lag 0; mean air pressure at the 30th value 1001.4 (pa) with RR of 9.052 (1.039-78.858) over lag 0 to 5; visibility at the 80th value 26.5 (km) with RR of 1.961 (1.005-1.423) over lag 0 to 2; average total cloud cover at the max value 100 (%) with RR 1.787 (1.014-3.148) over lag 0 to 2; sunshine duration at the 10th value 0.1 (h) with RR of 4.772 (1.018-22.361); daily evaporation shows no relationship in the cumulative result; daily average solar radiation at the minimum value 0 (W/m2) with RR of 5.588 (1.184-26.382). There is a relationship between wind speed and the onset of SBP, while mean air pressure, visibility, and average total cloud cover, especially sunshine duration and solar radiation which showed a strong effect, may be associated with severe clinical symptoms of SBP. Mean temperature and relative humidity may affect the course of SBP.

Nitric oxide regulates metabolism in murine stress erythroid progenitors to promote recovery during inflammatory anemia.

Inflammation skews bone marrow hematopoiesis increasing the production of myeloid effector cells at the expense of steady-state erythropoiesis. A compensatory stress erythropoiesis response is induced to maintain homeostasis until inflammation is resolved. In contrast to steady-state erythroid progenitors, stress erythroid progenitors (SEPs) utilize signals induced by inflammatory stimuli. However, the mechanistic basis for this is not clear. Here we reveal a nitric oxide (NO)-dependent regulatory network underlying two stages of stress erythropoiesis, namely proliferation, and the transition to differentiation. In the proliferative stage, immature SEPs and cells in the niche increased expression of inducible nitric oxide synthase ( Nos2 or iNOS ) to generate NO. Increased NO rewires SEP metabolism to increase anabolic pathways, which drive the biosynthesis of nucleotides, amino acids and other intermediates needed for cell division. This NO-dependent metabolism promotes cell proliferation while also inhibiting erythroid differentiation leading to the amplification of a large population of non-committed progenitors. The transition of these progenitors to differentiation is mediated by the activation of nuclear factor erythroid 2-related factor 2 (Nfe2l2 or Nrf2). Nrf2 acts as an anti-inflammatory regulator that decreases NO production, which removes the NO-dependent erythroid inhibition and allows for differentiation. These data provide a paradigm for how alterations in metabolism allow inflammatory signals to amplify immature progenitors prior to differentiation. Key points: Nitric-oxide (NO) dependent signaling favors an anabolic metabolism that promotes proliferation and inhibits differentiation.Activation of Nfe2l2 (Nrf2) decreases NO production allowing erythroid differentiation.

Dental-derived mesenchymal stem cell sheets: a prospective tissue engineering for regenerative medicine.

Stem cells transplantation is the main method of tissue engineering regeneration treatment, the viability and therapeutic efficiency are limited. Scaffold materials also play an important role in tissue engineering, whereas there are still many limitations, such as rejection and toxic side effects caused by scaffold materials. Cell sheet engineering is a scaffold-free tissue technology, which avoids the side effects of traditional scaffolds and maximizes the function of stem cells. It is increasingly being used in the field of tissue regenerative medicine. Dental-derived mesenchymal stem cells (DMSCs) are multipotent cells that exist in various dental tissues and can be used in stem cell-based therapy, which is impactful in regenerative medicine. Emerging evidences show that cell sheets derived from DMSCs have better effects in the field of regenerative medicine applications. Extracellular matrix (ECM) is the main component of cell sheets, which is a dynamic repository of signalling biological molecules and has a variety of biological functions and may play an important role in the application of cell sheets. In this review, we summarized the application status, mechanisms that sheets and ECM may play and future prospect of DMSC sheets on regeneration medicine.

Identification of nine signature proteins involved in periodontitis by integrated analysis of TMT proteomics and transcriptomics.

Recently, there are many researches on signature molecules of periodontitis derived from different periodontal tissues to determine the disease occurrence and development, and deepen the understanding of this complex disease. Among them, a variety of omics techniques have been utilized to analyze periodontitis pathology and progression. However, few accurate signature molecules are known and available. Herein, we aimed to screened and identified signature molecules suitable for distinguishing periodontitis patients using machine learning models by integrated analysis of TMT proteomics and transcriptomics with the purpose of finding novel prediction or diagnosis targets. Differential protein profiles, functional enrichment analysis, and protein-protein interaction network analysis were conducted based on TMT proteomics of 15 gingival tissues from healthy and periodontitis patients. DEPs correlating with periodontitis were screened using LASSO regression. We constructed a new diagnostic model using an artificial neural network (ANN) and verified its efficacy based on periodontitis transcriptomics datasets (GSE10334 and GSE16134). Western blotting validated expression levels of hub DEPs. TMT proteomics revealed 5658 proteins and 115 DEPs, and the 115 DEPs are closely related to inflammation and immune activity. Nine hub DEPs were screened by LASSO, and the ANN model distinguished healthy from periodontitis patients. The model showed satisfactory classification ability for both training (AUC=0.972) and validation (AUC=0.881) cohorts by ROC analysis. Expression levels of the 9 hub DEPs were validated and consistent with TMT proteomics quantitation. Our work reveals that nine hub DEPs in gingival tissues are closely related to the occurrence and progression of periodontitis and are potential signature molecules involved in periodontitis.

Growth or decay of a coherent structure interacting with random waves.

Solitary waves interacting with random Rayleigh-Jeans distributed waves of a nonintegrable and noncollapsing nonlinear Schrödinger equation are studied. Two opposing types of dynamics are identified: First, the random thermal waves can erode the solitary wave; second, this structure can grow as a result of this interaction. These two types of behavior depend on a dynamical property of the solitary wave (its angular frequency), and on a statistical property of the thermal waves (the chemical potential). These two quantities are equal at a saddle point of the entropy that marks a transition between the two types of dynamics: high-amplitude coherent structures whose frequency exceeds the chemical potential grow and smaller structures with a lower frequency decay. Either process leads to an increase of the wave entropy. We show this using a thermodynamic model of two coupled subsystems, one representing the solitary wave and one for the thermal waves. Numerical simulations verify our results.

Stress Erythropoiesis is a Key Inflammatory Response.

Bone marrow medullary erythropoiesis is primarily homeostatic. It produces new erythrocytes at a constant rate, which is balanced by the turnover of senescent erythrocytes by macrophages in the spleen. Despite the enormous capacity of the bone marrow to produce erythrocytes, there are times when it is unable to keep pace with erythroid demand. At these times stress erythropoiesis predominates. Stress erythropoiesis generates a large bolus of new erythrocytes to maintain homeostasis until steady state erythropoiesis can resume. In this review, we outline the mechanistic differences between stress erythropoiesis and steady state erythropoiesis and show that their responses to inflammation are complementary. We propose a new hypothesis that stress erythropoiesis is induced by inflammation and plays a key role in maintaining erythroid homeostasis during inflammatory responses.

Estrogen receptor 1 mutations in 260 cervical cancer samples from Chinese patients.

Cervical cancer is one of the leading causes of cancer-associated mortality among females; however, the underlying molecular mechanisms of its carcinogenesis remain largely unclear. Previous comprehensive genomic studies have revealed prevalent estrogen receptor 1 (ESR1) mutations in breast cancer, which are rare in certain other types of cancer. To the best of our knowledge, it is unknown whether ESR1 mutations also exist in cervical cancer. Considering the evidence that cervical cancer shares certain genetic aberrations with breast cancer, and that the progression of both breast and cervical cancers can be affected by estrogen, it is possible that cervical cancer may also harbor ESR1 mutations. In the present study, a total of 260 Chinese cervical cancer samples with distinct subtypes were tested for the presence of ESR1 mutations. A total of three heterozygous missense ESR1 mutations, p.K303R (c.908A>G), p.T311M (c.932C>T) and p.Y537C (c.1610A>G), were identified in 3/207 (1.4%) cervical squamous cell carcinoma samples, which were absent in 27 adenosquamous carcinomas and 26 adenocarcinomas samples. Of the three individuals with an ESR1mutation, 1 patient was also diagnosed with ovarian endometriosis and the other 2 patients were diagnosed with a uterine fibroid. A bioinformatics analysis suggested that these ESR1 mutations may be pathogenic by promoting the development of cervical cancer. Furthermore, a previous comprehensive study confirmed that individuals with cervical squamous cell carcinoma possessed ESR1 mutations. These combined studies indicate that ESR1 mutations may participate in the carcinogenesis of cervical squamous cell carcinoma, albeit at a low frequency. In conclusion, the present study identified three potentially pathogenic ESR1 mutations in Chinese cervical squamous cell carcinoma samples, but not in other subtypes.

Suppressor of fused (Sufu) promotes epithelial-mesenchymal transition (EMT) in cervical squamous cell carcinoma.

Suppressor of fused is essential for the maximal activation of Sonic Hedgehog signaling in development and tumorigenesis. However, the role of Sufu in cervical carcinoma remains unknown. Here, we report new findings of Sufu in regulating the epithelial-to-mesenchymal transition through the FoxM1 transcriptional modulation by 14-3-3ζ protein in cervical carcinoma. Sufu is overexpressed in cervical squamous cell carcinoma and its level in clinical tumor tissues is positively correlated with 14-3-3ζ. Functionanlly, siSufu remarkably prevents the cancer cell migration and invasion. We further demonstrate that the transcriptional activity of Sufu is increased by FoxM1, of which stability is promoted by 14-3-3ζ. Knockdown FoxM1 decreases the invasion of SiHa cells and reconstitution of Sufu rescues the invasion of these cells.Finally, overexpression of Sufu is significantly associated with differentiation grade, FIGO stage, Depth of stromal invasion and vascular cancer embolus. Our findings highlight a novel role for Sufu in cervical carcinogenesis.

The Effect of Probiotic Treatment on Patients Infected with the H7N9 Influenza Virus.

BACKGROUND: A novel avian-origin influenza A (H7N9) virus emerged and spread among humans in Eastern China in 2013. Prophylactic treatment with antibiotics and probiotics for secondary infection is as important as antiviral treatment. This study aims to assess the ability of probiotic treatment to restore internal homeostasis under antibiotic pressure and to reduce/ameliorate the risk of secondary infections resulting from infection with the H7N9 virus. METHODS: This is a retrospective study in archival samples. Between April 1 and May 10, 2013, 113 stool, sputum, and blood specimens were collected and analyzed by denaturing gradient gel electrophoresis (DGGE) to determine the composition of the patient microbiomes. Microbial diversity was calculated using Gel-Pro analyzer and Past software. Cluster analysis of DGGE pattern profiles was employed to create a phylogenetic tree for each patient, and multidimensional scaling (MDS) and principal component analysis (PCA) were performed to visualize relationships between individual lanes. RESULTS: Five patients had secondary infections, including Klebsiella pneumonia, Acinetobacter baumanii and Candida albicans infection. The DGGE profiles of fecal samples obtained at different time points from the same individual were clearly different, particularly for patients with secondary infections. Shannon's diversity index and evenness index were lower in all infected groups compared to the control group. After B. subtilis and E. faecium or C. butyricum administration, the fecal bacterial profiles of patients who had not been treated with antibiotics displayed a trend of increasing diversity and evenness. C. butyricum failed to reduce/ameliorate secondary infection in H7N9-infected patients, but administration of B. subtilis and E. faecium appeared to reduce/ameliorate secondary infection in one patient. CONCLUSION: H7N9 infection might decrease intestinal microbial diversity and species richness in humans. C. butyricum failed to reduce/ameliorate secondary infection in H7N9-infected patients. B. subtilis and E. faecium may also play a role in reducing/ameliorating secondary infection in these patients.

Angiotensin II plasma levels are linked to disease severity and predict fatal outcomes in H7N9-infected patients.

A novel influenza A (H7N9) virus of avian origin emerged in eastern China in the spring of 2013. This virus causes severe disease in humans, including acute and often lethal respiratory failure. As of January 2014, 275 cases of H7N9-infected patients had been reported, highlighting the urgency of identifying biomarkers for predicting disease severity and fatal outcomes. Here, we show that plasma levels of angiotensin II, a major regulatory peptide of the renin-angiotensin system, are markedly elevated in H7N9 patients and are associated with disease progression. Moreover, the sustained high levels of angiotensin II in these patients are strongly correlated with mortality. The predictive value of angiotensin II is higher than that of C-reactive protein and some clinical parameters such as the PaO2/FiO2 ratio (partial pressure of arterial oxygen to the fraction of inspired oxygen). Our findings indicate that angiotensin II is a biomarker for lethality in flu infections.

[Immunophenotypic analysis of leukemia promyelocytes in 71 patients with acute promyelocytic leukemia].

This study was purpose to investigate the immunophenotype of leukemia promyelocytes (LP) and its significance through retrospective analysis of LP immunophenotype and data in new diagnosis of patients with acute promyelocytic leukemia (APL). The immunophenotype of leukemia cells in 71 APL patients was analyzed by means of 6 color immunotyping. The results indicated that MPO, CD33 and CD13 were consistently expressed in leukemia cells of all APL cases with highest average percentages (> 88%) of positive cells among all studied markers. CD117 was found to be positive in 50.7%, and its average percentage of positive cells was 52.5%. Leukemia cells in about 10% cases expressed CD15 weakly, and its average percentage of positive cells was 42.5%. CD34 and HLA-DR showed decreased expressions in a small number of cases and were negative in the others. CD2 and CD56 were weakly expressed in nearly 25% APL cases, and the average percentage of positive cells were 39.3% and 42.3%, respectively. Thereby, it is of the opinion that the typical immunophenotype is characterized by MPO(+)CD13(+)CD33(+)CD117(±)CD15(±)CD34(-)HLA-DR(-) in APL. CD2 and CD56 were expressed significantly higher in CD34(+) or HLA-DR(+) group (including CD34(+) HLA-DR(+), CD34(+) HLA-DR(-) and CD34(-)HLA-DR(+)) than in CD34(-) and HLA-DR(-) group. Significant differences were also found in WBC and platelet counts, percentage of peripheral blood leukemic promyelocytes and the expression of CD13 among CD15 < 10%, 10% < CD15 < 20% and CD15 > 20% groups. It is concluded that the APL has a characteristic immunophenotypic profile, flow cytometric immunophenotyping may be considered as a useful tool for rapid recognition of APL and also may be considered to have an important significance for analysing origin of leukemic cells and clinical outcome of patients.