Theobroma cacao L.), caused by Moniliophthora perniciosa, is the most important limiting factor for the cacao production in Brazil. Hence, the development of cacao genotypes with durable resistance is the key challenge for control the disease. Proteomic methods are often used to study the interactions between hosts and pathogens, therefore helping classical plant breeding projects on the development of resistant genotypes. The present study compared the proteomic alterations between two cacao genotypes standard for WBD resistance and susceptibility, in response to M. perniciosa infection at 72 h and 45 days post-inoculation; respectively the very early stages of the biotrophic and necrotrophic stages of the cacao x M. perniciosa interaction.Witches’ broom disease (WBD) of cacao , oxidative stress regulation related proteins, and trypsin inhibitors. Interaction networks were predicted, and a complex protein-protein interaction was observed. Some proteins showed a high number of interactions, suggesting that those proteins may function as cross-talkers between these biological functions.T. cacao x M. perniciosa pathosystem. The important altered proteins identified in the present study are related to key biologic functions in resistance, such as oxidative stress, especially in the resistant genotype TSH1188, that showed a strong mechanism of detoxification. Also, the positive regulation of defense and stress proteins were more evident in this genotype. Proteins with significant roles against fungal plant pathogens, such as chitinases, trypsin inhibitors and PR 5 were also identified, and they may be good resistance markers. Finally, important biological functions, such as stress and defense, photosynthesis, oxidative stress and carbohydrate metabolism were differentially impacted with M. perniciosa infection in each genotype.We present the first study reporting the proteomic alterations of resistant and susceptible genotypes in the  Theobroma cacao L.), whose seeds are the raw material for chocolate production, is indigenous to the Amazon and Orinoco rainforests of South America, occurring in tropical climate regions such as Colombia, Mexico, Peru, Caribbean islands as well as African countries , and common spots . Through LC-MS/MS approaches, the identities of proteins that were obtained by analyzing the spectra generated with ProteinLynx Global software, were compared against the NCBI data bank and  were selBlast2Go tool was used to classify the proteins in 8 functional categories by their biological function. The majority-deregulated proteins in inoculated conditions for both genotypes in both times were associated with energy and metabolism. A significant amount of defense and stress related proteins were observed altered in inoculated treatment of TSH1188 compared to Catongo in 72HAI and 45DAI Fig. . It is i2O2 (hydrogen peroxide) accumulation and abscisic acid signaling [TSH1188 genotype at 72HAI exhibited important oxidative stress proteins up regulated such as glyceraldehyde-3-phosphate dehydrogenase C2 isoform 1 (spot 1123) and isoform 2 (spot 1122), and down regulation of peroxidases spot 1006, 1005)  as well as indirect  associations [To investigate the interactions among the differentially expressed proteins, 386 orthologous proteins previously identified in ciations . Eight i2O2 during the first 72 h in infected shoot apexes [Colletotrichum fragariae pathosystem [Plants during biologic stress may allocate energy to defense response against pathogens in detriment of other normal functions , which it apexes  and hight apexes  were obst apexes , 39. A shosystem .M. perniciosa. However, these findings cannot be properly compared to the results of the present study because the authors used different collection times from ours: a pool of samples to characterize early stage  and samples from 30 and 60 days. Nevertheless, proteomic and transcriptomic studies often have a weak correlation. This divergence can be explained mainly by post-translational modifications that proteins can undergo and directly influence the structure, location, degradation, metabolism, functions in addition to their stability. These modifications may also influence protein abundance, suggesting that the accumulation of proteins is partially determined by the accumulation and degradation of mRNAs [Considering that TSH1188 showed more spots compared to Catongo at both times and the metabolic shift from an inhibitory metabolism at 72HAI to an inductive metabolism at 45DAI  and hydroxyl radical (OH), are known to be toxic for plants, so they are removed by antioxidative enzymes. Nevertheless, they participate in important signaling pathways, such as development, growth, cell death, and mainly in response to biotic and abiotic stress, acting directly against the pathogens [A. thaliana [M. perniciosa increases significantly in the first 72HAI in TSH1188 compared to Catongo, which in turn did not vary [Oxidative oxygen species (ROS) such as superoxide O2athogens . Moreoveathogens . Furtherathogens . TSH1188athogens . This prathogens . Its cysathogens  and act thaliana . Hydrogenot vary . It was not vary .M. perniciosa at 45DAI in this pathosystem [2O2 levels at 45DAI were also observed in Catongo [2O2 in susceptible genotype may be related to promotion of pathogen life cycle [At 45DAI, TSH1188 showed up regulation of oxidative stress proteins twice as large as Catongo, particularly in proteins related to ROS detoxification  that binds with chitin immunogenic fragments, therefore prevents chitin-triggered immunity, evidencing a strategy of immune suppression of the host response by the pathogen. Moreover, PAMPs are expressed during biotrophic development and recent studies showed that Cerato-platanin, a PAMP from M. perniciosa, might bind chitin in a high affinity way, leading to an eliciting of plant immune system by fungal chitin released fragments [Fungal matrix cell wall is composed mainly by chitin, although the host did not produce this molecule, they developed, through evolution, enzymes (e.g chitinases) that are capable to degrade the fungus cell wall during defense response . In the ragments , 60. Furragments , are up Fusarium oxysporum sp. and transgenic potato x Macrophomina phaseolina and Phytophthora infestans [M. perniciosa (biotrophic to saprophytic) by releasing nutrients to fungal mycelium [M. perniciosa at the biotrophic phase release lytic proteins and proteases that contributes to the pathogenicity [The resistance response of TSH1188 was also highlighted by the expression of several PRs, mainly at 45DAI, that shows representatives of four families. PRs are a heterogeneous group of proteins with basal expression in plants that are induced mainly during pathogen infection , 63. Gesnfestans , 68. In nfestans , 70 whicmycelium . Furthermycelium , 72, wermycelium . In addigenicity .. In cacao, the accumulation of these serine protease inhibitors varies in different tissues and genotypes in response to several stress. It was highly represented in the RT library of the resistant interaction between T. cacao and M. perniciosa [, and in cacao leaves also varies in response to heavy metal stress [M. perniciosa are deuterolysins, a type of fungal metalloproteinases that are similar to bacterial thermolysin [M. perniciosa, we believe that it is an important plant defense response of cacao genotypes to stress, that in this case might act protecting the cacao cells against the fungal hydrolases.The serine protease inhibitors are widely distributed in living organisms like, fungi, plants, bacteria and humans. Further, it has been related to plant resistance . In cacarniciosa . These irniciosa , zygoticrniciosa  and cacarniciosa , and in l stress . The mosrmolysin . NeverthM perniciosa is one of the most important pathogens to cacao trees and to understand the biological processes underlying the proteomic mechanisms during infection is mandatory. Thus, a detailed protein-protein interaction network is highly demanded. Construction of predict PPI networks are challenging for non-model plants, [M. perniciosa we have utilized homology-based prediction to identifying PPI among differentially expressed proteins identified in the pathosystem. It is important to emphasize that, some proteins that were identified as isoforms in the 2D-PAGE electrophoresis, were identified as the same protein in the course of the identification process, which diminish the total number of identifications in the PPI networks due to duplicity of the input. plants, , 79 espeM. perniciosa infection on the metabolism of TSH1188 and Catongo are illustrated in the Fig. M. perniciosa infection, which can help us better understand how these undelaying mechanisms are connected, enabling to predict new functional interactions. This is very important, once available information about PPI in non-model plants is scarce. Similar maps were constructed in other pathosystem, such as, soybean and Fusarium virguliforme [M. perniciosa infection. Besides, one of the correlations found between some of these proteins was co-expression. It is known that co-expressed genes are often functionally related, ‘guilt by association’ [Proteins are not solitary entities; rather, they function as components of a complex machinery, which functional connections are determinant to general metabolism. The effects of uliforme  and may uliforme . A layerciation’ , and mayThese results provide hints about the molecular mechanisms of resistance and susceptibility in the pathosystem. Although these predicted interaction networks still need to be verified and further analyzed in following investigations, it is known that PPI are broadly conserved between orthologous species , 84, strT. cacao genotypes differing in response against M. perniciosa infection. Here it was possible to follow the proteomic changes resulting from early and late biotrophic phase interaction in both susceptible and resistant models, identifying more than 500 proteins involved in important biological functions. It was also observed that these functions are distinctly altered between genotypes, and possibly is related to resistance in THS1188, which presented a high number and variety of proteins in response to infection compared to Catongo. The study highlighted important proteins that may be related to key functions in resistance such as oxidative stress proteins especially in TSH1188 that showed a strong mechanism of detoxification. Also, positive regulation of defense and stress proteins were more robust in this genotype during early and late response to infection, based on identified proteins with important roles against fungus, such as chitinases, trypsin inhibitors and PR 5. These proteins may be good resistance markers. Finally, biologic important functions such as stress and defense, photosynthesis, oxidative stress and carbohydrate metabolism were differentially impacted in a proteomic level by M. perniciosa in each genotype.This is the first study using 2D-PAGE associated with LC MS/MS in investigation of T. cacao genotypes during M perniciosa infection are provided, highlighting new potential targets for further investigation.Based in these findings, here is suggested a model showing the main alterations observed in both genotypes during infection Fig. . A promihttp://www.ceplac.gov.br/). They were planted in a mixture of commercial potting mix  and clay-rich soil, in a 2:1 proportion, and grown in sterile substrate in a greenhouse under natural light and 90% relative humidity until the inoculation day. The International Cacao Germplasm Database – ICGD (http://www.icgd.rdg.ac.uk/) provides further information on TSH 1188  and Catongo .The plant material used in this study was chosen based on its demonstrated resistance (TSH1188) and susceptibility (Catongo) to WBD from field progeny trials . Seedlin, from CEPLAC/CEPEC, Ilhéus, Bahia, Brazil, accession number 4145 . The inoculum was prepared as described by Mares and colleagues (2016) [− 1. Inoculation was carried out in a moist chamber for 48 h in a dark . After inoculation, the seedlings were transferred to a greenhouse and irrigation for 20 min three times a day until the end of the experiment. The quality of the inoculation was done by assessing by checking the spore germination prior and 24 h after inoculation (≥80% germination). The control seedlings of each genotype were mock inoculated with the same solution without inoculum.The shoot apex of the plantlets was inoculated with a basidiospore suspension of inoculum Mp4145s (2016) . Three tEach seedling was evaluated weakly for broom type, stem swelling and death. Shoot apexes were collected (around 40) from inoculated and non-inoculated (mock inoculated) experiments from both THS1188 and Catongo at each time point; 72 h after inoculation (72HAI) and 45 days after inoculation (45DAI). All collected shoot apexes were immediately frozen in liquid nitrogen and then lyophilized, followed by protein extraction and proteomic evaluation. The inoculated experiments from each genotype were compared with its matching and non-inoculated control. The remaining plants were used for disease evaluation.Shoot apexes were submitted to protein extraction using chemical and physical methods to optimize the protein yield in accordance with the protocol developed by Pirovani and colleagues (2008)  with modThe protein profile quality of shoot apexes was evaluated using 20 μg of protein submitted to SDS-PAGE gels  in vertical electrophoresis system (Omniphor).− 1, Tris-HCl pH 8.8 75 mmol L− 1, glycerol 30%, SDS 2%, bromophenol blue 0.002%) with DTT 10 mg mL− 1 for 15 min, and alkylated using equilibrium buffer with iodoacetamide 25 mg mL− 1 for 15 min. Finally, strips were equilibrated with running buffer  for 15 min. The second dimension was carried out in polyacrylamide gels 12.5% (triplicates) and the electrophoresis running were performed in the HOEFER SE 600 Ruby  vertical electrophoresis system under the following parameters: 15cmA/gel for 15 min, 40 mA/gel for 30 min and 50 mA/gel for 3 h, or until complete migration of sample trough the gel. After fixation and coloration with colloidal Comassie Brilliant Blue (CBB) G-250, gels were decolorized with distillated water. The digitalization process was made using ImageScanner III , the images were analyzed, and the spot detection was made by matching the gels triplicates in silico using Image Master 2D Platinum software .To the 2D analyses, 500 μg of proteins were applied in immobilized pH gradient (IPG) gel strips of 13 cm with pH range of 3–10 NL . The isoelectric focusing was carried out in the Ettan IPGphor 3  system, controlled by Ettan IPGphor 3 software. Electrofocusing conditions: rehydration time – 12 h at 20 °C; Running - 500Vh for 1 h, 1000Vh for 1:04 h, 8000Vh for 2:30 h and 8000Vh for 40 min. The strips were reduced using equilibrium buffer (urea 6 mol Lp ≤ 0.05 and ≥ 1.5-Fold change). A multivariate analysis was performed to evaluate the global changes of genotypes in response to infection. Spots intensities values were obtained through digitalization results and were used to find the hierarchical clustering of replicates using NIA array analysis tool (http://lgsun.grc.nia.nih.gov/ANOVA/) software. In addition, a principal component analysis (PCA) was performed to identify the phenotypic and genotypic differences between treatments.The statistical analysis was made comparing the inoculated to non-inoculated treatments (ANOVA) to identify the differentially (exclusive and common) expressed spots (Micromass Q-TOFmicro (WATERS) spectrometer as described by Mares and colleagues (2016) [ProteinLynx Global Server v 2.3 e (WATERS) software and compared against the NCBI data bank, using MASCOT MS/MS Ions Search (www.matrixscience.com) tool, following the search criteria: Enzyme: Trypsin; Allow up to 1 missed cleavage; Fixed Modifications: Carbamidomethyl (C); Variable Modifications: Oxidation (M); Peptide Tolerance: 30 ppm; MS/MS tolerance: 0.3 Da and 0.1 to fragmented ions. Spectra not identified at NCBI were compared to the Theobroma cacao databank (http://cocoagendb.cirad.fr/gbrowse) via ProteinLynx using the same criteria. In this work we consider the protein exclusively found in the not inoculated treatments as down regulated, assuming that its accumulation rates were reduced under detection limits as well as, to the protein exclusively found at inoculated treatments considered up regulated.The selected protein spots were manually excised from gels and individually bleached, washed, dehydrated and submitted to protein digestion as described by Silva and colleagues (2013)  Peptidess (2016) . SpectraProteinLynx were available in the platform. Biologic function, biologic process and location of proteins were accessed using BLAST2GO (http://www.blast2go.com/) software.FASTA sequences of identified proteins were obtained in the NCBI databank using the access number generated by MASCOT. The sequences of proteins identified in the T. cacao and A. thaliana of differentially expressed proteins identified in both times to both genotypes during the interaction were searched based on the local alignment of the sequences using BlastP 2.5.0 [A. thaliana were considered as orthologous. The PPI analyzes were predicted using Retrieval of Interacting Genes/Proteins (STRING) 10.0 version [www.string-db.org). In the software, all analyses were carried against A. thaliana database. PPI information was obtained enabling different prediction methods in the software, such as neighborhood, experiments, co-expression, gene fusion, databases, and co-occurrence. Associations were visualized with a medium confidence cutoff (0.400) using A. thaliana as standard organism.Before the PPI analyses, orthologous proteins between tP 2.5.0  with she version   highlighting the TSH1188 genotype in 45DAI infected with M. perniciosa. Total proteins extract (500 μg) were focused on IPG strips (13 cm), pH ranging from 3 to 10 NL, separated by SDS-PAGE (12.5%) and stained with CBB G-250.Additional file 2. Principal Component Analysis showing the grouping of samples regarding different treatments. In A, biplot for all treatments of the Catongo genotype. B, biplot for all treatments of the TSH1188 genotype. C, biplot for all treatments of the two genotypes analyzed together. Each dot represents a triplicate, named as follows: Initial sequence letters representing the genotypes, followed by the numbers represented by the treatment period, 72HAI and 45DAI and the final letters representing the inoculated (I) and not inoculated (N) treatment.Additional file 3. Venn diagrams representing the total number of spots detected in both genotypes and treatments. Spots are discriminated by their occurrence: Gray dashed circles represent non-inoculated treatments; black circles represent inoculated treatments. In the diagram’s intersections the total number of common spots and the number of common significantly altered with FC ≥ 1.5 are shown.Additional file 4. List of complete differentially Expressed Proteins identified in TSH1188.Additional file 5. List of complete differentially Expressed Proteins identified in Catongo.Additional file 6. Subcellular localization of identified proteins. The analysis was performed in the Blast2Go software. Subcellular localization from identified proteins of Catongo (A) and TSH1188 (B) genotypes at 72HAI. Subcellular localization from Catongo (C) and TSH1188 (D) genotypes at 45DAI.Additional file 7. Differentially expressed proteins of TSH1188 and Catongo during interaction with M. perniciosa subjected PPI analysis. Networks of up regulated (A) and down regulated (B) proteins in TSH1188 at 72HAI. Networks of up regulated (C) and down regulated (D) proteins in Catongo at 72HAI. Network nodes represent proteins in which each node represents all the protein by a single protein-coding gene locus. Small nodes indicate proteins of unknown 3D structure, large nodes indicate proteins which 3D structures are known or predict . Different line colors indicate the types of evidence for the associations. Query proteins not connected with network were removed for better visualization.Additional file 8. Complete list of orthologous proteins subjected to PPI analysis.Additional file 9. Detailed protein extraction method.


Orientia tsutsugamushi and Rickettsia typhi) (10.8% vs. 0.3%), dengue virus (7.7% vs. 0.5%), Leptospira (4.8% vs. 0.8%), adenovirus (4.8% vs. 1.0%), and enterovirus (2.1% vs. 0%) (p < .05). The real proportion of dengue in AUF cases was underestimated because patients with dengue-positive rapid diagnosis tests were excluded from the study. The emerging agent Rickettsia felis, which had not been previously observed in Vietnam, was detected in this study. In total, 216 patients (57.1%) were given causative diagnoses, comprising 143 (66.2%) monoinfections and 73 (33.8%) coinfections. The infections caused by these agents should be considered in clinical practice and further studies. Additionally, agents susceptible to doxycycline were detected in 15.6% of AUFs; thus, this drug should be included in the panel used to treat AUF patients.Acute undifferentiated fever (AUF) is frequently observed in tropical settings, but diagnosing the cause of AUF is often a challenge for local physicians and the physicians treating returning travellers. We conducted a case-control study in central Vietnam in 2016. A total of 378 febrile adult patients (AUFs) with a fever for ≤21 days, no evidence of localized infection and negative screening tests for dengue and malaria, and 384 afebrile adult patients (Controls) were prospectively enrolled. Whole blood, plasma, eschar swab, throat swab and urine specimens were collected and analysed. Quantitative PCR and RT-PCR were used to test for 55 bacteria, viruses and their subtypes. Serological tests were also used to test for rickettsial agents. The most common aetiology was influenza virus (20.9% in AUFs vs. 0% in Controls), followed by rickettsial agents (mainly  Acute undifferentiated fever (AUF) is a temporary febrile illness accompanied by nonspecific manifestations . It is fPlasmodium vivax (33.4%), Plasmodium falciparum (26.5%), Leptospira (9.4%), influenza virus (8.9%), Dengue virus (6.3%) and rickettsial agents (4.1%), but a significant proportion of malaria parasites and Leptospira were also observed in the control group  AUFs and 100 [26.0%] Controls). Haemophilus influenzae (73 [19.3%] AUFs and 61 [15.9%] Controls) and Streptococcus pneumoniae (50 [13.2%] AUFs and 41 [10.7%] Controls) were also commonly detected. Some less common bacteria, including Staphylococcus aureus, Mycoplasma pneumoniae and Moraxella catarrhalis, were also found in a small number of AUFs and Controls. No significant difference in the proportion of bacteria detected in throat swabs was found between AUFs and Controls.We also investigated the relationship between the occurrence of viruses and bacteria in AUFs, but the correlation test showed no correlation among the detected viruses and bacteria (Table S2).O. tsutsugamushi was present as the single pathogen in 19 patients and was accompanied by Leptospira in two patients. Influenza virus was the most frequently observed in codetection cases  with one additional pathogen  or two additional pathogens . Adenovirus (n = 9), enterovirus (n = 2) and coronavirus 229E (n = 1) were also observed in combination with other viruses or bacteria. Other codetections included the detection of two or three bacteria in throat swabs, and S. pneumoniae, K. pneumoniae and H. influenza were the most frequently observed bacteria in these cases.A substantial proportion of pathogen codetection was identified in this study. p < .05). Patients with murine typhus had febrile durations (8.5 [6–10] days) longer than those of patients with other diagnoses (except those with scrub typhus), and patients with leptospirosis presented a medium course of fever (5.5 [4–7] days). Patients with dengue fever exhibited lower WBC and PLT counts than nearly all the patients with other diagnoses (p < .05). Cough was more frequently observed in patients with influenza (63.6%) than in patients with other diagnoses (p < .05). Patients with noninfluenza respiratory viral infection were young, and cough (21.4%) was observed less frequently in these patients than in patients with influenza.Analyses of the clinical characteristics of patients who presented with single scrub typhus, murine typhus, leptospirosis, dengue fever, influenza and other respiratory viral infections are described in R. felis was detected in two patients, who presented with continuous mild fever, a peak body temperature of 38°C–38.5°C, headache, and normal WBC, PLT, AST and ALT levels. One individual had an eschar with a 5 × 8-mm, painless, centred black crust surrounded by a red halo on the right side of his face  patients for a course of 5–10 days. Among these patients, most  received one antibiotic, and the others  received a combination of two or three antibiotics. Among the monotherapy cases, amoxicillin was the most commonly used antibiotic , followed by doxycycline , 2nd/3rd-generation cephalosporin , fluoroquinolones , macrolides , and antimalarial drugs . The most common combination antibiotic therapy was 2nd/3rd-generation cephalosporin and a fluoroquinolone , followed by 2nd/3rd-generation cephalosporin and doxycycline .R. felis) received anti-rickettsial antibiotics . With the exception of one case of codetection of scrub typhus and leptospirosis, only six of the remaining 17 (35.3%) patients with leptospirosis received the appropriate antibiotics . All the patients with influenza were not given anti-influenza agents, but approximately half of them  received an antibacterial agent . None of the patients died, and all the patients who either received an appropriate or inappropriate antibiotic had recovered completely from their illnesses at the time of discharge.Twenty-nine of 41 (70.7%) patients with a rickettsial infection   and coronavirus [n = 2]) were considered probable causes in this study because they were detected in patients who presented with cough, breathlessness or sore throat. RSV is the most common cause of acute respiratory infection in young children , H. influenzae [n = 36], S. pneumoniae [n = 24], S. aureus [n = 4], M. pneumoniae [n = 3], and M. catarrhalis [n = 2]) detected in AUF patients presenting with accompanying respiratory symptoms were considered probable causes of AUF. With the exception of these probable cases, most of the detected bacteria might be considered colonizing bacteria. However, we noticed that K. pneumoniae, which is known to be associated with pneumonia, urinary tract infection and, particularly in Asia, pyogenic liver abscesses [The bacteria in throat swabs were detected at similarly high proportions in AUFs and Controls. Some cases of bacteria . Accordingly, eschar and a high ALT level (>80 IU/L) were associated with scrub typhus, whereas a high AST level (>80 IU/L), a long fever duration (>7 days) and a job as a farmer were associated with non-scrub typhus rickettsial infections. Only splenomegaly was associated with leptospirosis. Haemorrhage, low WBC count (<4 k/µL) and low PLT count (<150 k/µL) were associated with dengue infection. The presence of cough was associated with influenza, whereas a young age (<30 years) was associated with noninfluenza respiratory viral infection. Although a limited number of cases were included in each logistic regression model, we believe that these results might be useful for local clinicians who care daily for patients with AUF but have limited diagnostic tools to differentiate some common causes of AUF from other causes.Even though we were able to detect aetiologies in a large number of AUFs, this study has some limitations. The sampling period was limited to 4 months, which does not provide information on the seasonal circulation of aetiologies. The serological test was not applied for all pathogens except rickettsial agents, which might have led to missed diagnoses of some infections. Finally, blood culture was not performed regularly due to the limited facilities during the sampling in local laboratories. Thus, we might also have missed some typhoid cases and some other bacteria, as they were found in 1–8% in studies in which blood culture was used routinely ,59.Epidemiological studies on fever aetiologies in the rural tropics are highly needed. The extensive and systematic workup of this study provided unique data on the causes of AUF in Vietnam because we used reference methods and local afebrile subjects as controls, which allowed us to better clarify differences between infection and colonization. These data have implications for the management of patients with AUF in Vietnam and even Southeast Asia. We recommend that in addition to RDTs for dengue and microscopy for malaria, local hospitals should be equipped with diagnostic tools  for rickettsial infections, leptospirosis, and influenza. More importantly, a significant proportion  of the causative agents of AUF are susceptible to doxycycline. Therefore, this drug needs to be included in the panel used to treat patients with AUF. Empirical treatment with a combination of β-lactam (e.g. ceftriaxone) and doxycycline might be used to treat AUF patients with a severe clinical presentation because some agents detected here could result in fatality.This prospective case-control study was conducted from May to August 2016 at four major general hospitals in Quang Nam province – a rural area located in central Vietnam . These included Quang Nam Central General Hospital, Quang Nam Provincial General Hospital, Quang Nam Northern Mountainous Region General Hospital and Quang Nam Regional General Hospital, which have approximately 2130 beds combined and serve 1,487,700 residents of Quang Nam province and thousands of people in the neighbouring districts of Quang Ngai province.All patients who met the eligibility criteria during the study period were continuously enrolled. AUFs were included in this study if they fulfilled four primary criteria: (i) age ≥15 years; (ii) axillary temperature ≥38°C; (iii) duration of fever ≤21 days ; and .All clinicians and nurses who participated in this study were trained on the study protocol and sample collection. A clinician examined the patients and invited them to participate in the study if they met the eligibility criteria. In particular for the AUFs, all the patients were screened for dengue infection by RDTs, and the patients who came from a malaria endemic area were screened using a peripheral blood smear. Accordingly, only AUF patients who were negative for these diseases were included in this study. After obtaining written informed consent from the participants, the clinicians recorded their vital signs, signs and symptoms of the current illness, their history of exposure to the forest within 30 days, chronic comorbidity diseases and basic clinical laboratory results on a case report form (CRF). A nurse collected a total of 3 mL of whole blood, divided into 1 mL of whole blood in an EDTA tube and approximately 1 mL of plasma in a dry tube after centrifugation, and 1 mL of urine from each participant. One throat swab specimen was taken by a clinician and preserved immediately into a viral transport medium. The clinician also collected eschar swab specimens if the patient presented with one or several eschars based on a previously described method . In addiFor each patient, 200 µL of whole blood and 200 µL of urine were used for DNA extraction, and 200 µL of acute-phase plasma and 200 µL of the throat swab sample in viral transport media were used for DNA/RNA extraction. The eschar specimens were pretreated and used for DNA extraction as previously described . DNA extO. tsutsugamushi, Rickettsia spp., R. felis, R. typhi, Anaplasma spp., Bartonella spp., Borrelia spp., and C. burnetii (Table S4). These DNA products were also tested by qPCR for Leptospira spp., Salmonella spp., Salmonella enterica serovar Typhi/Paratyphi, Shigella spp., S. aureus, S. pneumoniae, Streptococcus pyogenes, Tropheryma whipplei and Burkholderia pseudomallei. The DNA products isolated from the eschar swab specimens were tested for O. tsutsugamushi, Rickettsia spp., R. felis and R. typhi, whereas the DNA products isolated from urine specimens were tested for Leptospira spp. using specific qPCR systems. The DNA/RNA products obtained from the plasma samples were tested by real-time reverse-transcription PCR (qRT-PCR) for dengue viruses , chikungunya virus, Zika virus and hantaviruses . The Eurogentec Takyon qPCR kit  was used for bacterial DNA detection, and the LightCycler® Multiplex RNA Virus Master  was used for viral RNA detection.The DNA products isolated from the whole blood specimens were tested using quantitative real-time PCR (qPCR) with genus-specific primers and probes targeting specific sequences of ® respiratory pathogens-33 kit  was used to detect various respiratory viruses, bacteria and fungi in the DNA/RNA products obtained from throat swabs. The targeted pathogens were influenza A virus; influenza B virus; influenza C virus; influenza A (H1N1) swl virus; human parainfluenza viruses 1, 2, 3 and 4; human coronaviruses NL63, 229E, OC43 and HKU1; human metapneumoviruses A/B; human rhinovirus; human RSV A/B (RSV A/B); human adenovirus; enterovirus; human parechovirus; human bocavirus; M. pneumoniae; Chlamydia pneumoniae; S. pneumoniae; H. influenzae; H. influenzae type B; S. aureus; M. catarrhalis; Bordetella spp.; K. pneumoniae; Legionella pneumophila/longbeachae; Salmonella spp.; and Pneumocystis jirovecii. PCR assays were performed with a CFX ConnectTM Real-Time PCR Detection System . Negative control and positive controls for the corresponding pathogens were included in each run. The PCR procedures were performed according to the manufacturer’s instructions. Quantitative PCR and quantitative reverse-transcription PCR assays were considered positive if the cycle threshold  was <35. All the AUFs and Controls were tested in the same panel of these pathogens.The Multiplex TaqMan real-time PCR using the FTDOrientia tsutsugamushi serotypes Karp, Kato, and Gilliam; Rickettsia typhi; Rickettsia felis, Rickettsia conorii and another SFG rickettsiae; and Coxiella burnetii as previously described [R. conorii; IgM titre >1:32 for other rickettsial antigens; IgG titre >1:128; IgG titres >1:64 for other rickettsial antigens [Rickettsia spp. in cases that were not differentiated by IFA due to cross-reactivity of relevant antigens of Rickettsia spp. [The acute- and convalescent-phase plasma samples from all the patients with AUF were subjected to specific indirect immunofluorescence (IFA) assays to detect antibodies of escribed . An IFA antigens ,62. Westsia spp. ,61.χ2 test and Fisher’s exact test. Student’s t-test, the Wilcoxon–Mann–Whitney test and the Kruskal–Wallis test were used to compare different continuous variable between the groups. A p-value of less than .05 was considered statistically significant.The data were entered and verified using Microsoft Excel software and analysed using Stata version 12.0  and R version 3.1.3 . The categorical variables are summarized as frequencies and percentages. Different groups were compared using the This study was approved by the Ethical Review Committee of the Quang Nam Central General Hospital of the Ministry of Health, Vietnam . All the patients included in this study provided written informed consent.


Sarcoidosis is a systemic inflammatory disease characterized by the presence of noncaseating granulomas in different organs. Sarcoidosis associated with monoclonal gammopathy of undetermined significance (MGUS) is a rare finding with only 10 cases reported to date. We describe a 79-year-old male patient who presented with dry mouth for 4 months. Lip biopsy done prior to admission showed nonnecrotizing epithelioid cell granulomas. On admission, laboratory analysis was significant for elevated calcium, decreased parathyroid hormone, increased erythrocyte sedimentation rate, undetectable parathyroid hormone-related peptide (PTHrp), mildly decreased 25-hydroxyvitamin D, elevated 1,25-dihydroxyvitamin D, elevated angiotensin converting enzyme, and positive Bence Jones protein in the urine. Serum protein electrophoresis showed an elevated gamma globulin level at 38% and an IgG monoclonal gammopathy with an M-spike of 1.47. Bone marrow biopsy was consistent with MGUS. The patient showed significant improvement with steroids and was discharged with close follow-up from nephrology and oncology. Salivary gland involvement in patients with sarcoidosis is a rare finding. Our case is a valuable addition to the small number of cases described in the literature supporting an association between plasma cell disorders and sarcoidosis. Larger prospective studies are needed to determine if a true association between the two diseases exists. Sarcoidosis is a systemic inflammatory disease characterized by the presence of noncaseating granulomas in different organs. The most common affected sites include the lungs, skin, and lymph nodes. Patients may be asymptomatic or may have a wide variety of clinical manifestations depending on the organs involved. Persistent cough, generalized weakness, fever, night sweats, peripheral lymphadenopathy, erythema nodosum, fatigue, and incidental chest radiograph abnormalities are the most common disease manifestations. The nonspecific clinical picture of sarcoidosis often leads to a late diagnosis of the disease .An association between sarcoidosis and malignant neoplasms has been described in the literature . SarcoidWe describe a patient who presented with dry mouth and was later found to have concurrent sarcoidosis and MGUS.A 79-year-old male with a past medical history of hypothyroidism and benign prostatic hyperplasia presented with dry mouth for four months. Family history was significant for the presence of Crohn's disease and systemic lupus erythematosus (SLE) in his sister. He was initially referred to an oral surgeon who performed a lip biopsy two weeks prior to admission revealing nonnecrotizing epithelioid cell granulomas. The patient was prescribed a mouthwash solution containing diphenhydramine, nystatin, lidocaine, hydrocortisone, and tetracycline. He was referred to a rheumatologist. His xerostomia significantly worsened prior to his appointment with rheumatology so he decided to go to the emergency department (ED). He presented to the ED with generalized weakness and decreased oral intake secondary to mouth pain resulting in a 30-pound weight loss over four months. Physical exam was remarkable for dry oropharyngeal mucosa. Laboratory analysis revealed an elevated serum calcium of 12.71 mg/dL (reference range: 8.4–10.7 mg/dL), an increased ionized calcium of 1.9 mmoL/L (reference range: 1.10–1.30 mmoL/L), an increased creatinine level of 3.81 mg/dL (reference range: 0.7–1.3 mg/dL), a decreased parathyroid hormone level of 6.5 pg/mL (reference range: 15–65 pg/mL), and an increased erythrocyte sedimentation rate (ESR) of 55 mm/hr (reference range: 0–15 mm/hr). Despite adequate fluid hydration, his calcium level remained elevated. Further workup for hypercalcemia revealed undetectable parathyroid hormone-related peptide (PTHrp), mildly decreased 25-hydroxyvitamin D at 18.1 ng/ml (reference range: 20–100 ng/ml), and an elevated 1,25-dihydroxyvitamin D at 72 pg/ml (reference range: 18–64 pg/ml).Further workup for hypercalcemia showed an elevated angiotensin-converting enzyme at 91 U/L (reference range: 18–53 U/L). Bence Jones protein revealed free lambda light chains in the urine. Serum protein electrophoresis showed an elevated gamma globulin level of 38% and an IgG monoclonal gammopathy with an M-spike of 1.47. Immunoglobulin free light chain revealed elevated kappa free light chains at 5.79 and elevated lambda free light chains at 14.1 with a kappa to lambda ratio of 0.4. A bone marrow biopsy was done and was sent for pathology.Further workup for dry mouth showed positive antinuclear antibody (ANA) at a titer of 1 : 160, and the other rheumatologic workup was negative.The constellation of findings prompted further workup for sarcoidosis. Chest radiograph (CXR) showed minimal hilar lymphadenopathy which was more pronounced on the right side, bibasilar infiltrates and mild bilateral pleural effusions. High-resolution computerized tomography (HRCT) of the chest showed prominent hilar densities, ground glass opacities, and bilateral pleural effusions . He was Sarcoidosis is a chronic inflammatory disease of unknown etiology. It is thought to occur secondary to exaggerated immunologic response to environmental factors in genetic susceptible patients. The diagnosis is made by clinical and radiological criteria, histopathological finding of noncaseating granulomas, and absence of alternative diagnoses. The pathophysiology involves activation of different arms of the immune system including lymphocytes, macrophages, and antigen-presenting cells . Upon exThe presentation of sarcoidosis in our patient was atypical in several ways. Sarcoidosis most commonly affects patients between 20–40 years of age. Persistent cough, generalized weakness, fever, night sweats, peripheral lymphadenopathy, erythema nodosum, fatigue, and incidental chest radiograph abnormalities are the most common disease manifestations. Our patient was 79 years old and presented with dry mouth, both of which are atypical for sarcoidosis. Orofacial sarcoidosis is a rare finding. Common orofacial symptoms of sarcoidosis include pain, nasal obstruction, loosening of the teeth, swelling of the mandible, and localized swelling and ulcers of the oral cavity. A few case series reported oral involvement as an initial presentation of the disease –18. In aSarcoidosis is divided into 5 stages based on CXR findings  20]. In. In20]. Patients with sarcoidosis have an increased risk for developing cancer of the lung, stomach, small intestine, liver, and lymphoid tissues. The relative risk of developing lymphoid malignancies was found to be 13.2% in patients with sarcoidosis , 25.The simultaneous occurrence of sarcoidosis and plasma cell disorders is a rare finding. To the best of our knowledge, only 10 cases have been reported thus far . The casThere are no epidemiologic data to our knowledge to support the increased risk of plasma cell disorders in patients with sarcoidosis. It is suggested that dysregulation of the immune system may induce development of autonomous plasma cell clones and result in the uncontrolled production of the monoclonal immunoglobulins. Activation of CD4 positive T helper cells, suppression of CD8 positive T regulatory/suppressor cells, and increased cytokine production may contribute to the continuous stimulation of B cells, causing monoclonal or polyclonal hypergammaglobulinemia  [8]. ThiThe annual risk of progression of MGUS to multiple myeloma (MM) is approximately 1% in general population. Up to 16% of patients with MGUS may develop MM after >30 years. Risk factors for progression per Mayo Criteria include an M-protein level >1.5 g/dL, Non-IgG isotype (IgA or IgM), and an abnormal Kappa-Lambda free light chain ratio (<0.26 or >1.65). Monitoring for progression to MM depends on the number of risk factors present. Patients with no risk factors are recommended to repeat serum protein electrophoresis (SPEP) in 6 months and every 2-3 years thereafter. Patients with 1 or more risk factors are recommended to check serum LDH, B2 microglobulin, C-reactive protein, and bone marrow biopsy at time of diagnosis, in addition to a CT abdomen for patients with IgM subtype to rule out Waldenström's macroglobulinemia. If all tests are unremarkable, these patients should monitor complete blood count (CBC), SPEP and creatinine in 6 months and then, yearly for life . PatientIn conclusion, we describe a patient who presented with dry mouth and was diagnosed simultaneously with MGUS and sarcoidosis. Salivary gland involvement in patients with sarcoidosis is a rare finding. Our patient was treated with steroids which resulted in symptomatic improvement. Our case is one of few others in the literature describing concurrent plasma cell disorders and sarcoidosis. Larger prospective studies are needed to determine if an association between the two diseases exists and define the nature of association and whether causality exists.


This study aimed to determine the seroprevalence of anti-HAV IgG in Thai medical students in 2016 compared with the previous data and to demonstrate the cross-effective strategy to screen HAV seropositivity.Sera from 176 first-year medical students  at a university hospital in Thailand were tested for anti-HAV IgG. Data from HAV vaccination records and questionnaires were also collected. HAV seropositivity was unexpectedly high . 37.5% (n = 66) had an HAV vaccination record. Of these, 60.6% received the full HAV vaccination series, 4.5% received one HAV vaccination, 34.8% did not receive HAV vaccination, and 3.0% had natural HAV immunity. The long-term efficacy of HAV vaccination was at least 97.5% over a mean of 15.55 ± 2.44 years. There was a significant difference in immunity between students with (66.7%) and without (50.9%) vaccination records (P = 0.028). Most of the student’s parents had a bachelor’s degree or higher  and above average income . Parental education and socioeconomic status influenced vaccination accessibility in these medical students. Screening of vaccination records instead of routine anti-HAV IgG testing is a cost-effective and reliable strategy to determine HAV immunity in medical students in Thailand. Hepatitis A virus (HAV) infection is the major cause of acute viral hepatitis worldwide, including Thailand . Unlike The prevalence of HAV infection in developing countries is high due to inadequate sanitation and poor personal hygiene. In the past, HAV was endemic in Thailand, but the rate of HAV infection has been declining, especially in the young, which has led to a large seronegative population . Thus, tHealth care personnel working in hospitals are considered as a high-risk group. Active immunoprophylaxis is recommended to prevent HAV outbreaks in hospitals. However, universal vaccination for all is costly and unnecessary for seropositive persons. Anti-HAV IgG testing has been suggested, and subsequent immunization has been encouraged for all seronegative individuals , 6.Our study aimed to determine the seroprevalence of anti-HAV IgG in medical students and compare the results with those collected in 1982, 1992, 1996 and 2001 , 8. The Sera samples from first-year medical students at Chulalongkorn University collected between March, and June 2016 were screened for the protective antibody against HAV infection. All available medical student vaccination records were assessed for the timing and number of HAV vaccines that the students received. Medical students and their parents received questionnaires regarding each student’s history of HAV vaccination or natural infection and demographic data .Results of this HAV seropositive prevalence were compared with the results of our three previous studies which were conducted in 1982 , 1996 8 also repFirst-year medical students with blood tests as a compulsory routine check-up for hepatitis B markers  and anti-varicella zoster virus (VZV) IgG provided written consent to use the rest of the sera sample for anti-HAV IgG testing. Ethics approval was granted by the Ethics Committee, Faculty of Medicine, Chulalongkorn University (IRB Number: 614/60).Anti-HAV IgG was assessed by enzyme-linked immunosorbent assay  following the manufacturer’s instructions. The sensitivity and specificity of the tests were 100% and 100%, respectively. These results were reported as seropositive or seronegative.P-value < 0.05 was considered statistically significant.All statistical analysis was performed using SPSS version 24.0.0 . Continuous and categorical data were presented as mean ± SD. Unpaired t-tests and Chi squared tests were used for between-group comparisons of the continuous and categorical data, respectively. A There were 176 medical students recruited into the study  and 126 (71.6%) students completed and returned the questionnaires. These questionnaires demonstrated that most of the students’ parents graduated with a Bachelor’s degree or higher  and the mean annual income per capita was 17,000.76 ± 194.22 USD  had anti-HAV seropositivity. Sixty-six (37.5%) students had their HAV vaccine history documented in vaccination records. Of these, 40 (60.6%) received two HAV vaccine injections (complete HAV vaccine series), 3 (4.5%) received one HAV vaccine injection, and 23 (34.8%) did not receive any HAV vaccine injections. Of the 23 that did not receive any HAV vaccines, 2  had natural HAV immunity.The long-term seroprevalence (at or above a protective level) among those who received the completed HAV vaccine series was 97.5%. The mean duration between the first HAV injection and anti-HAV IgG testing was 15.55 ± 2.44 years. For students whose vaccination records were not available, 56 (50.9%) had HAV immunity. There was a significant difference in detectable HAV immunity between medical students who had vaccination records and those who did not  of all and 49.1% (N = 66) in a subgroup of medical students who did not have vaccination records. As medical students have a risk of exposure to infectious agents including HAV, a strategy to detect the immunity is needed. HAV vaccine and other vaccine-preventable diseases should be managed by immunization when seronegative students start practicing in hospitals.In our university hospital, for more than a decade, have implemented a policy of routinely checking immunity to hepatitis B and Varicella virus among the first-year medical students. Seronegative students then receive hepatitis B and Varicella vaccines. Serologic testing for anti-HAV IgG is not routinely carried out among medical students due to the high cost of HAV vaccines and no significant benefit for HAV vaccination with screening from cost–benefit analyses studied in Thailand , which mIn conclusion, the present study, the seroprevalence of HAV immunity among Thai medical students in 2016 was very high compared to the previous seroprevalence trend. HAV immunization can explain this high seroprevalence, rather than natural HAV infection. Vaccination records were shown to be important, as documented vaccinations had a good correlation with the results of anti-HAV IgG testing. Parents’ high levels of education and income may explain the high level of access to HAV vaccines. Screening of vaccination records before anti-HAV IgG testing or HAV immunization can be considered a cost-effective method for preventing HAV infection among medical students in Thailand and other countries with a similar pattern of HAV epidemiology.No socioeconomic, parental education or vaccination data for medical students from the previous studies were available for comparison. The ELISA kit used to determine the anti-HAV IgG in the present study was different from the previous study. However, the diagnostic values following the manufacturer’s data were excellent in both ELISA kits with the sensitivity and specificity > 99%.


Findings remain unclear whether neutrophil-to-lymphocyte ratio (NLR) detrimentally affects advanced nasopharyngeal carcinoma (NPC) prognosis. We aim to evaluate the prognostic value of NLR in patients with NPC based on a large-scale cohort from an endemic area.We selected patients retrospectively from a cohort examining long-term cancer outcomes following diagnosis. Neutrophil counts and lymphocyte counts were assessed prior to treatment. Kaplan–Meier method and log-rank test were used to calculate and compare survival outcomes. Additionally, Cox proportional hazards model was utilized to carry out univariate and multivariate analyses.P < 0.001), distant metastasis-free survival , and progression-free survival  than NLR ≤2.50. In multivariate analysis, NLR was found to be a significant prognostic factor for OS , DMFS , and PFS .Between October 2009 and August 2012, we enrolled 1550 consecutive NPC patients staged II-IVB. The median value of NLR was 2.27 . Determined by operating characteristic curve using overall survival (OS) as an endpoint, the cutoff value for NLR was 2.50. At 5 years, NLR > 2.50 was associated with inferior OS (90.3% vs 82.5%; Pretreatment NLR independently affects survival. Our findings suggest that NLR measurements will be of great clinical significance in the management of NPC. In Southern China, nasopharyngeal carcinoma (NPC) is a common malignancy. Previous literature reported the annual incidence rate varied from 15 to 50 cases per 100,000 . Plasma Prior literature has shown systemic inflammatory response stimulates cancer metastasis and progression by facilitating angiogenesis and inhibiting apoptosis . An impoTo fill this gap in knowledge, we investigated the long-term prognostic effect of NLR on the outcome of patients with NPC using a large-scale homogenous patient cohort.NPC patients treated by radiotherapy with curative intent from October 2009 through August 2012 were identified. This retrospective study with prospectively collected data included a cohort of 1550 men and women. Patients were included if (1) histologically confirmed NPC; (2) had no prior history of malignancy; (3) absence of distant metastasis; (4) stage II-IVA disease according to the 8th edition of the American Joint Committee on Cancer (AJCC) staging system; (5) did not receive prior treatment for NPC; (6) complete pretreatment history of hematological variables; and (7) no infection or inflammatory conditions.http://www.researchdata.org.cn), and was assigned the RDD approval number RDDA2017000386. If someone need to access the data, he/she should obtain our consent, and have to explain the source of the data in their study.All included patents had undergone routine pretreatment evaluations comprising of medical history, complete physical examination, complete blood count, fiber-optic nasopharyngoscopy, chest radiography, abdominal sonography, magnetic resonance imaging (MRI) of the nasopharynx and neck, and bone scan or whole-body fluorodeoxyglucose positron emission tomography. Patients were restaged in accordance to the 8th edition of the AJCC staging system for NPC . The preAbsolute neutrophil and lymphocyte counts were assessed before treatment and determined utilizing a Sysmex XE-5000 automated hematology analyzer . We calculated NLR as the absolute counts of neutrophil divided by the absolute lymphocyte counts.2/day over 120 h) with cisplatin (80 mg/m2), or cisplatin (80 mg/m2) with docetaxel (80 mg/m2) administered at three week intervals for 3 cycles. Concurrent chemotherapy consisted of cisplatin (80 or 100 mg/m2) given in weeks 1, 4, and 7 of RT, or cisplatin (40 mg/m2) given weekly during RT, beginning on the first day of RT.Intensity-modulated radiotherapy (IMRT) was used for treating primary tumor and the upper neck area above the caudal edge of the cricoid cartilage. Using a previously described treatment protocol by our institution, target volumes were delineated  in agreeWe selected the primary endpoint as overall survival (OS), and secondary endpoints included distant metastasis-free survival (DMFS), locoregional relapse-free survival (LRFS), and progression-free survival (PFS). We calculated overall survival from initial treatment to death. For distant and locoregional relapse-free survival analyses, we recorded the latencies  to the first remote or locoregional relapse respectively. We calculated progression-free survival from the date of initial treatment to the date of treatment failure or death from any cause, whichever was first. Patients were seen every three months during the first 2 years, every six months for years 3 through 5, and annually thereafter until death. The duration of patient follow-up was measured from the first day of therapy to either the day of last examination or the day of death.2 test. Receiver operating characteristic (ROC) curve analysis was used to evaluate the cutoff point for NLR. Cumulative survival rates were depicted by Kaplan–Meier curves and compared by Log-rank tests for each dichotomized biomarker. Univariate and multivariate analysis utilizing a Cox proportional hazards model was used to test the independent association of different factors by backward elimination. All statistical analysis were 2-tailed, and P < 0.05 was determined statistically significant. All statistical analyses were completed using R 3.1.2.For categorical variables, we calculated relative frequencies (percentage), while for continuous variables we calculated median (interquartile range [IQR]). Additionally, categorical variables were compared using χTable P < 0.001)   . N stage  and NLR  were also associated with DMFS; and only age  was associated with LRFS . Additionally, N stage  was an independent risk factor for DMFS; and age was a significant predictor for LRFS  . Using OS as the endpoint, the cutoff value for NLR was 2.50, determined using ROC curve. At 5 years, patients with NLR >  2.50 had significantly inferior OS  and also patients with advanced disease . However, no significant differences were observed between groups regarding age, sex, family history, history of alcohol consumption, or treatment strategy  and low NLR (≤ 2.50). Additionally, we examined the correlations between NLR and various clinicopathological features. Patients that smoked generally had higher NLR , and indicated that NLR > 2.50 was significantly associated with inferior PFS.In an analysis by Templeton and colleagues  on NLR aN = 380) from two controlled trials, but were unable to determine if NLR adds prognostic value for NPC. The first potential reasoning is that different NLR levels have different prognostic value. In the study by Chua et al., NLR was dichotomized into binary variables using the median value of NLR stratified patients, but failed to use ROC curve, which is confirmed to be a central or unifying position in the process of assessing and using diagnostic tool to analyze the optimum cutoff point [Conversely, Chua et al.  examinedff point , 21. Secff point  found paElevated NLR was recognized as a significant risk factor in patients with NPC. However, the mechanisms underlying this observation remains largely unclear. One possibility might be that high NLR serves as a marker for up-regulated inflammatory processes within the host microenvironment that potentially promote the development of more aggressive tumor clones –24. AnotP = 0.001; N stage, P = 0.015; overall stage, P < 0.001). This suggests NLR contributes to patient stratification by providing additional information about disease burden. Of interest, our results indicate that individuals that smoke commonly had higher levels of NLR. It is plausible that the variations of NLR were influenced by smoking-related inflammation [The associations between NLR and TNM stage have previously been reported. Based on findings from prior studies that reported a positive association of NLR with TNM stage , we applammation .A major limitation in the present study is that we did not collect information on other hematologic markers of inflammation, such as lymphocyte-monocyte ratio (LMR) and C-reactive protein , 28. AnoIn summary, pretreatment NLR independently affects survival for advanced NPC. Increasing NLR > 2.50 was mostly detrimental to OS, DMFS, and PFS in patients with advanced NPC. Additionally, pretreatment NLR may serve as a cost-effective prognostic factor in patients with NPC, and pretreatment NLR measurements will be of great clinical significance in the management of NPC.


Background: Despite a potential link between immunoglobulin E (IgE) levels and cardiovascular disease, the effect of elevated total IgE levels on long-term mortality risk remains unclear. We prospectively investigated the association between total serum IgE levels and all-cause and cardiovascular mortality in US adults. Methods: We analyzed data from the 2005–2006 National Health and Nutrition Examination Survey (NHANES) and the NHANES (2005–2006) Linked Mortality Public File. The 2005–2006 NHANES data of 1496 older adults aged ≥50 years and who underwent a serum total IgE antibody test in the initial survey were included. Results: After a median follow-up of 119 months, a significant association was observed between total serum IgE levels and cardiovascular mortality, with subjects with the highest total IgE exhibiting a 3.19-fold  increase in the risk of cardiovascular mortality compared with those with the lowest total IgE (≤16.80 kU/L). Furthermore, the mortality rate increased with an increase in total IgE levels, regardless of baseline history of cardiovascular diseases . Conclusions: This finding suggests that the elevation of IgE levels may be a risk factor for increased cardiovascular mortality.  Immunoglobulin E (IgE) is a class of antibodies synthesized and released by the B lymphocytes of the immune system through interactions among genes, cytokines, and the environment . IgEs caTherefore, this study aimed to prospectively investigate the association between total serum IgE levels and all-cause and cardiovascular mortality in the general US population. Furthermore, mortality associated with elevated total IgE levels in the presence and absence of cardiovascular disease at baseline was investigated. http://www.cdc.gov/nchs/nhanes.htm).Study data was retrieved from the 2005–2006 National Health and Nutrition Examination Survey (NHANES) and from the NHANES (2005–2006) Linked Mortality Public File from the United States . The NHAIn total, 2011 participants aged ≥50 years and who underwent a serum total IgE antibody test in the initial survey were included from the 2005–2006 NHANES data and the Linked Morality File. Of these, 515 older adults were excluded because of missing questionnaire information . The study’s final cohort included 1496 older adults from the 2005–2006 NHANES database.http://www.cdc.gov/nchs/data/nhanes/nhanes_05_06/al_ige_d.pdf).Serum samples were collected and were analyzed for total IgE allergen using the Pharmacia Diagnostics Immuno CAP 1000 System . A detailed description of laboratory and quality control procedures can be obtained on the NHANES 2005–2006 webpage  codes were used for all causes of mortality. Based on the underlying causes of mortality from ICD-10, codes I00–I09, I11, I13, I20–I51 were attributed to cardiovascular diseases.2 and was categorized in four groups: <18.5 kg/m2 (underweight), 18.5–24.9 kg/m2 , 25–29.9 kg/m2 (overweight), and ≥30.0 kg/m2 (obese). Regarding disease history, hypertension was defined as systolic blood pressure ≥ 140 mm Hg and diastolic blood pressure ≥ 90 mm Hg, use of antihypertensive drugs or previous physician-diagnosed hypertension. Hypercholesterolemia was defined as a total serum cholesterol level of ≥240 mg/dL or physician-diagnosed hypercholesterolemia. Diabetes was defined as a fasting plasma glucose level of ≥6.99 mmol/L, non-fasting plasma glucose level of ≥11.1 mmol/L, current insulin use, or prior physician diagnosed diabetes. Presence of allergic disease was based on previous allergies, as diagnosed by a physician or health professional.Baseline characteristics were retrieved from 2005–2006 NHANES interview data and included age , sex, ethnic background , education , family income , smoking status , and moderate physical activity (yes or no). Body mass index (BMI) was calculated by dividing the estimated weight in kg by the measured height in mp-value was calculated using the log-rank test. The null hypothesis was that there is no difference in survival among IgE quartiles. The log-rank test compares the observed number of deaths in each quartile group and the number expected if the null hypothesis were true. Cox proportional hazard regression was conducted to evaluate the association among total IgE levels and all-cause and cardiovascular mortality. The association between total IgE levels and mortality was further assessed in terms of the presence or absence of baseline cardiovascular diseases, including heart failure, coronary heart disease, heart attack, and angina [Significant differences in participants’ characteristics were evaluated using the chi-square test. Total serum IgE levels were categorized into quartiles: Quartile 1 (≤16.80 kU/L), Quartile 2 (16.81–44.10 kU/L), Quartile 3 (44.11–123.00 kU/L), and Quartile 4 (≥123.01 kU/L). After the stratification of total IgE quartiles, Kaplan–Meier curves for cumulative mortality rates were presented according to the total IgE quartiles. The d angina . Hazard Weighted estimates of population parameters were computed according to the National Center for Health Statistics to account for the complex sampling design. All analyses were performed using the PROC SURVEY procedures in SAS 9.3  and R . Statistical significance was set at α = 0.05 (two-sided).2), and not practice moderate physical activity. Regarding baseline conditions, significant differences were observed between the two groups with respect to the presence of hypertension and diabetes mellitus.p = 0.0226) and were marginally elevated in subjects who die owing to cardiovascular disease .p-value = 0.0005), but not all-cause mortality.p-values > 0.05). In contrast, subjects without cardiovascular diseases at baseline showed greater risk for cardiovascular mortality in Quartile 2  and Quartile 4 .Using a prospective US representative cohort, a significant association was observed between total serum IgE levels and cardiovascular mortality after a median follow-up of 119 months. Participants with elevated total IgE levels (≥123.01 kU/L in Quartile 4) had a 3.19-fold higher cardiovascular mortality risk than those with low total IgE levels (≤16.80 kU/L in Quartile 1). Subjects without history of baseline cardiovascular diseases  were at greater risk of cardiovascular mortality in terms of increases in the total IgE levels. Taken together, total IgE levels did not significantly predict overall mortality, but the elevation of total serum IgE levels may be a risk factor for cardiovascular mortality among older adults (≥50 years).p for linear trend <0.0001) [To the best of our knowledge, no previous studies have investigated the association between cardiovascular mortality risk and total IgE levels. The findings of this study are consistent with results of previous studies highlighting the IgE-mediated association between cardiovascular diseases and subsequent events . Criqui <0.0001) .A significant association between elevated IgE levels and some forms of cardiovascular diseases appear to be prospectively confirmed. Langer et al. (1996) conducted a prospective study with 621 subjects  for approximately 9 years. They found a significantly increased ischemic heart disease risk (relative risk (RR) = 3.4; 95% CI: 1.4–8.4) and non-fatal AMI development  in males with baseline IgE levels of ≥200 kU/L compared with those with low baseline IgE levels) . A studyDespite scientific evidence showing the function of total IgE in increased cardiovascular events, the causality dilemma is as baffling as the chicken and egg problem . In partThis is the first study to report a significant association between total IgE levels and cardiovascular mortality risk based on the high-power and reliable nationwide NHANES 2005–2006) data. However, limitations of this study should be addressed. The NHANES Linked Mortality File provides mortality data from death certificates. This approach may overestimate the burden of cardiovascular events as the cause of mortality, particularly at older ages [05–2006 dIn summary, we found that older adults with elevated IgE levels had a higher cardiovascular mortality risk than those with lower IgE levels. The risk was predominant in subjects without cardiovascular diseases at baseline than in those with baseline cardiovascular diseases. These findings suggest that elevated IgE levels may be a risk factor for increased cardiovascular mortality.


The assessment of Idiopathic Pulmonary Fibrosis (IPF) using HRCT requires great experience and is limited by a significant inter-observer variability, even between trained radiologists. The evaluation of HRCT through automated quantitative analysis may hopefully solve this problem. The accuracy of CT-histogram derived indexes in the assessment of survival in IPF patients has been poorly studied.CO and age was created to test their prognostic value in assessing survival. Through ROC analysis, threshold values demonstrating the best sensitivity and specificity in predicting mortality were identified. They were used as cut-off points to graph Kaplan-Meier curves specific for the CT-indexes.Forty-two patients with a diagnosis of IPF and a follow up time of 3 years were retrospectively collected; HRCT and Pulmonary Function Tests (PFTs) performed at diagnosis time were analysed; the extent of fibrotic disease was quantified on HRCT using kurtosis, skewness, Mean Lung Density (MLD), High attenuation areas (HAA%) and Fibrotic Areas (FA%). Univariate Cox regression was performed to assess hazard ratios for the explored variables and a multivariate model considering skewness, FVC, DLp = 0.03, p = 0.01, p = 0.02, p = 0.02 and p = 0.017 respectively). Skewness demonstrated the lowest Akaike’s information criterion value (55.52), proving to be the best CT variable for prediction of mortality. Significant survival differences considering proposed cut-off points were also demonstrated according to kurtosis (p = 0.02), skewness (p = 0.005), MLD (p = 0.003), HAA% (p = 0.009) and FA% (p = 0.02) – obtained from quantitative HRCT analysis at diagnosis time.Kurtosis, skewness, MLD, HAA% and FA% were good predictors of mortality (HR 0.44, 0.74, 1.01, 1.12, 1.06; CT-histogram derived indexes may provide an accurate estimation of survival in IPF patients. They demonstrate a correlation with PFTs, highlighting their possible use in clinical practice. Idiopathic pulmonary fibrosis (IPF) is a rare pulmonary disease characterized by a progressive fibrosis of the lungs that leads to the inexorable worsening of lung function . IPF is ILD assessment using HRCT requires great experience and is limited by a significant inter-observer variability, even between trained radiologists . In the A more objective evaluation of HRCT through automated quantitative analysis may hopefully solve this problem. Recent studies started exploring this second possibility using, in most cases, complex algorithms, able to perform texture analysis. However, although very promising, texture analysis requires high computational steps, currently reserving its use for a research setting. To date, only a few studies have focused on CT-histogram evaluation, which is a different quantitative analysis method requiring fewer computational steps than texture analysis. These characteristics of objectivity and relative simplicity make this analysis potentially usable and reproducible in a realistic clinical setting.Therefore, the aim of this study is to evaluate in a real-life work setting, the prognostic value of histogram-based quantitative HRCT variables in predicting mortality in a cohort of patients affected by IPF.A retrospective analysis of our interstitial lung disease (ILD) database identified a total of 210 patients who had received a multidisciplinary team (MDT) diagnosis of IPF according to 2011 ATS/ERS/JRS/ALAT IPF guidelines over a period of three years (January 2012 to August 2015) [This study received approval the ethical committee of Policlinico-Vittorio Emanuele Hospital of Catania.CO)) were performed according to the ATS/ERS guidelines using Vmax Sensor Medics [p = 0.19).All clinical information was obtained from medical records. PFTs  and Diffusing Capacity for carbon monoxide  - based image processing software for automatic lung parenchyma segmentation was used to calculate HRCT quantitative parameters. This tool has been developed in the MATLAB R2016a simulation environment , running on iMac  with Mac Operating System OS X El Capitan.HRCT attenuation histogram was extracted after automatic lung parenchyma segmentation using region growing algorithm to include voxels between − 200 Hounsfield units (HU) and − 1.024 HU. kurtosis, Mean Lung Density (MLD), skewness, High Attenuation Areas (HAA) % and Fibrotic Areas (FA) % were subsequently calculated , median (interquartile range) or as percentage of the relative frequency as appropriated. Wilcoxon test for unpaired data was used to assess differences between baseline and follow up time. Reported data were adjusted using Holm’s correction. Spearman’s rank correlation was used to assess relation between CT-histogram based variables. Univariate and multivariate Cox proportional hazard regression analysis were performed to assess Hazard Ratios for predictors of survival. Akaike’s information criterion (AIC) was used to estimate the relative quality of the statistical models. Kaplan-Meier survival analysis was used to assess overall survival while ROC analysis was used to assess sensitivity and specificity. All the statistical analyses were performed using STATA/IC 14.2 version. A The study evaluated 42 consecutive subjects with an MDT diagnosis of IPF. Thirty-five were male (83.33%) and 7 were female 16.67%). There were 33 (78.57%) former/current smokers and 9 (21.43%) never-smokers. The mean age at diagnosis was 68.26 ± 6.34 years. The mean follow up time was 1037 ± 430 days. Thirty-height (90.48%) patients were treated only with pirfenidone while 4 (9.52%) switched from pirfenidone to nintedanib because of drug-related adverse events. A total of 10 patients (23.33%) died during the follow up period. All demographic, PFTs and CT-derived variables at baseline are summarized in Table 6.67%. Thp = 0.25, p = 0.25, p = 0.40, p = 0.40, p = 0.68, p = 0.88, p = 0.21 respectively) . Similarly, also kurtosis, skewness, MLD, HAA% and FA% were good predictors of mortality . Results of univariate Cox hazard regression are summarized in Table Univariate Cox proportional hazard regression analysis demonstrated, as expected, that both FVC% and DLAkaike’s information criterion (AIC) was calculated to estimate relative quality of the statistical model. Skewness demonstrated the lowest AIC value (AIC = 55.52)  (see Table p = 0.05), a sensitivity of 80% and a specificity of 75% for a threshold value of ≤1.15 of skewness , a sensitivity of 70% and a specificity of 78% for a threshold value of > − 762.97 of MLD , a sensitivity of 80% and a specificity of 62.5% for a threshold value of > 14.76 of HAA%  and a sensitivity of 80% and a specificity of 62.5% for a threshold value of > 24.26 of FA%  in predicting mortality.A multivariate model was created considering FVC, DLes AIC = 6.86  every 10 mm of intervals while Best et al. analysed (1 mm thick) scans every 20 mm . Best etFor this reason, in our study, we tried to re-evaluate the predictive value of CT histogram indexes in assessing survival, analysing 1 mm thick scans without interval in a homogeneous cohort of consecutive IPF patients treated with antifibrotics and with a follow up time of 3 years.Univariate Cox proportional analysis, as in previous studies, demonstrated that kurtosis, skewness, MLD, HAA% and FA% are significant predictors of mortality. Of all of these, skewness demonstrated the lowest AIC value and, according to our analysis, should be considered as the best CT histogram derived variable in predicting mortality. We also evaluated sensitivity and specificity of these variables with respect to mortality. Based on this, we identified possible cut-off points that we used to graph Kaplan-Meier curves. Although these cut-off points were extracted from a relatively small number of patients and need a validation in larger-group cohorts, we demonstrated how CT-variables and cut-off points may help in identifying patients with different life expectations. This finding could greatly help the clinician in the management of patients, especially if they are not able to correctly perform PFTs.CO and age in predicting mortality in a Multivariate model. As shown in Table CO, which was confirmed as a strong predictor of mortality.We also tested the role of skewness, FVC, DLOur study also evaluated changes after 12 ± 3 from baseline in a small subgroup of 23 patients. Differently from the study of Best et al., no difference was demonstrated, neither for CT quantitative variables nor for FVC changes. A possible explanation of this finding could reside in the treatment the patients received. In our study, subjects homogeneously received antifibrotic therapy resulting in a relative functional and radiological stability after one year. To our knowledge this represents the first study analysing patients treated with pirfenidone and nintedanib with this approach.This study has some strengths. We analysed the entire volume of the lungs taking into account every thin section in the final calculation of the indexes; every exam was performed with the same protocol and in the same CT-scanner both at baseline and follow up; all patients were treated with antifibrotic drugs reproducing a real clinical setting; patients were followed for a long enough period to assess survival.This study, however, also has several limitations. The retrospective design and the single-centre nature of the study represent the first great limitation. We also analysed a small number of patients, even if only the study of Best et al. considered a truly greater number of patients with this method. Our analysis considered HRCT scans performed with the same protocol and in the same CT-scanner. This is the reason for the exclusion of a large number of newly-diagnosed IPF patients over the considered period. Moreover, as is known, this kind of analysis may be greatly influenced by the level of inspiration of the patients. An incorrect manoeuvre or the presence of artifacts may erroneously affect quantitative CT indexes. Given the retrospective nature of the study, we did not used a spirometric control during acquisition to ensure an optimal inspiration. However, all CT-scans were reviewed and approved for the inclusion in the study by our radiologists. Another notable and previously mentioned limitation of the study includes the need for some computational steps required for the image processing to get the CT-indexes.Based on our results, baseline HRCT indexes are able to provide a prediction of survival and can be used as a surrogate marker for prognosis. Given the characteristics of simplicity, objectivity and reproducibility, this method could actually help the clinician and the radiologist in the evaluation of sub-clinical changes and the prognosis of patients in daily clinical practice. Further studies with larger cohorts and an external validation are needed to confirm these data.


Pseudomonas aeruginosa (PA) is a leading cause of nosocomial infections, and carbapenem non-susceptible strains are a major threat to patient safety.A single center, retrospective comparative analysis of carbapenem-non-susceptible PA (CnSPA) and carbapenem-susceptible PA (CSPA) bloodstream infections (BSIs) was conducted between January 1, 2007, and December 31, 2016. Prevalence and risk factors associated with CnSPA BSIs were examined.N = 101) of patients had CnSPA. High APACHE II scores (≥15), central venous catheterization, and delayed application of appropriate definitive therapy were independently associated with higher risk of mortality in PA BSIs. Multivariate analysis revealed that respiratory disease and exposure to carbapenems within the previous 90 days to onset of BSI were independent risk factors for acquisition of CnSPA BSIs. Overall all-cause 30-day mortality associated with PA BSIs was 26.8% (91/340). In addition, mortality was higher in patients with CnSPA than in those with CSPA . Corticosteroid therapy and delayed receipt of effective definitive therapy were independent risk factors for death from CnSPA BSIs.The study enrolled 340 patients with PA BSIs; 30.0%  contains supplementary material, which is available to authorized users. Pseudomonas aeruginosa (PA) is responsible for 10–15% of nosocomial infections worldwide [orldwide . Such inorldwide .Carbapenems are regarded as a drug of last resort and are used to treat severe infections caused by multidrug-resistant PA. However, increasing use of carbapenems has increased the prevalence of carbapenem-non-susceptible (CnS) PA strains. Moreover, such strains are often resistant to other drugs such as β-lactams and quinolones . AccordiPrevious studies show that inappropriate antimicrobial therapy and/or delayed initiation of effective antimicrobial therapy is associated with an adverse outcome , 10. HowHere, we aimed to identify risk factors for CnSPA BSIs and evaluate clinical treatment responses and factors associated with mortality in patients with PA BSIs or CnSPA BSIs.This retrospective cohort study was carried out at The First Affiliated Hospital of Zhejiang University, a 2500-bed tertiary teaching hospital for adults in Zhejiang, China. The study focused on episodes of PA BSI occurring between January 1, 2007, and December 31, 2016. Episodes of BSI were identified from the clinical microbiology laboratory database. Patient data  were retrieved from patient charts. The inclusion criteria were as follows: (i) patients aged ≥18 years; (ii) the first episode of PA BSI occurred during the study period; and (iii) patients met the diagnostic criteria for BSI [Demographic and clinical and microbiological data were retrieved from the electronic medical records system. The following data were collected: age; gender; underlying disease according to a crude Charlson Comorbidity Index (CCI) ; duratioThe probable source of BSI was determined according to the definitions for nosocomial infections document published by the Centers for Disease Control . PrimaryAntimicrobial susceptibility of PA was determined using the Vitek2 system. The guidelines of the Clinical and Laboratory Standards Institute standards 2017) define carbapenem non-susceptibility as a minimum inhibitory concentration of ≥4 μg/ml imipenem or meropenem [17 defineP value < 0.05 was considered statistically significant. All statistical analyses were performed using SPSS version 24.0. The survival distribution function was estimated using the Kaplan-Meier product limit method. Nonparametric (log-rank and Wilcoxon) tests were used to compare survival functions between groups.Continuous variables are expressed as the mean ± standard deviation (assessed using Student’s t test) or as the median (range)  when the distribution was not normal. Categorical variables are expressed as percentages and were analyzed using the Chi-squared test or two-tailed Fisher exact test as appropriate. The strength of associations was determined by calculating the odds ratio (OR) and 95% confidence intervals (CIs). Two-tailed tests were used to determine statistical significance. All-cause in-hospital mortality was examined by logistic regression analysis. A Pseudomonas aeruginosa (CSPA) strains. Data for both groups are summarized in Table P = 0.011). Over the past 10 years, the incidence of PA BSI has fluctuated from 0.027/1000 patient-days to 0.062/1000 patient-days, with the highest incidence occurring in the ICU (1.85/1000 patient-days); this proportion neither rose nor declined year on year (P = 0.180) . The overall 30-day attributable mortality rate was 21.5% (73/340). The 30-day attributable mortality rates were similar among patients infected with CnSPA  or CSPA  (P = 0.125).During the study period, there were 832 episodes of PA BSI , or to have undergone hemodialysis (P < 0.05), blood transfusion (P < 0.05), or a nonsurgical invasive procedure . In addition, they were more likely to have respiratory tract infection (most probable infectious source), higher Pitt scores, and longer hospitalization days after BSI than those with CSPA. There was no significant difference between the groups in terms of APACHE II scores at onset of BSI. Also, patients with CnSPA were more likely to have been exposed to antibiotics during the 90 days prior to BSI onset (P = 0.001).Univariate logistic analysis of patients with CSPA or CnSPA BSI Table  revealedP < 0.001), exposure to carbapenems in the 90 days prior to onset of BSI , and exposure to antifungal agents in the 90 days prior to onset of BSI .Multivariate logistic regression analysis Table  identifiP < 0.001), to have a high APACHE II score , and to have hypoalbuminemia. The rate of carbapenem non-susceptibility in non-survivors was higher than that in survivors.Of the 340 patients enrolled, 249 (73.2%) were classified as survivors and 91 (26.8%) as non-survivors. Univariate logistic analysis  and APACHE II score ≥ 15 points . Independent factors that reduced the risk of mortality were appropriate definitive therapy , definitive therapy with BLBLIs , and receipt of prompt appropriate therapy (within 24 h) . The 30-day survival curve analysis revealed no significant difference in mortality between the CnSPA and CSPA groups (P = 0.143) , a respiratory tract infection as the probable infectious source, hypoalbuminemia, and a high APACHE II score at onset of BSI . Multivariate logistic regression analysis . Receipt of prompt appropriate definitive therapy (within ≤24 h) improved survival .Of the 101 patients with CnSPA BSIs, 63 62.4%) were classified as survivors and 38 (37.6%) as non-survivors. The 30-day mortality rate was 37.6%, and the average hospitalization time was 54 days. Univariate analysis showed that, compared with survivors . Finally, 80 (79.2%) patients received definitive treatment; of these, 55 received monotherapy, although there was no significant difference in mortality between those receiving definitive monotherapy and those receiving definitive combination therapy . Fifty-one patients (50.5%) received appropriate definitive therapy. Forty-one (40.6%) patients received one active drug, and 10 (9.9%) patients received at least two active drugs. There was no significant difference in mortality between those receiving appropriate definitive therapy and those receiving inappropriate definitive therapy   received empirical therapy and 30 (30.0%) received appropriate empirical therapy. In addition, 65 64.4%) patients received empirical monotherapy and 16 (15.8%) received combination therapy. There was no significant difference in mortality between those receiving empirical monotherapy and those receiving empirical combination therapy . Exposure to antibiotics, especially monotherapy, can cause drug resistance (and even multidrug resistance) due to production of antibiotic-inactivating enzymes, low permeability of the bacterial outer membrane, overexpression of various efflux pumps, and loss of the outer membrane protein [P < 0.001). Moreover, patients exposed to antifungals are more likely to have received antineoplastic and immunosuppressive agents, broad-spectrum antibiotics, prosthetic devices and grafts, and more aggressive surgery [Hospitalized patients often have a record of prior exposure to antibiotics or immunological system defects . Moreover, subgroup analysis of appropriate monotherapy revealed that survival rates after treatment with BLBLIs and carbapenems were still similar . In addition, there was no significant difference in survival rates after definitive therapy with BLBLIs or carbapenems . As mentioned previously, inappropriate therapy is an independent risk factor for a poor prognosis [There is no consensus regarding treatment of PA BSIs , 35. A rrognosis . The prorognosis . Therefo11. Our own findings are consistent with the above results. Of note, Kim et al. found that appropriate combination therapy was associated with better outcomes than appropriate monotherapy for patients with febrile neutropenia [p = 0.085). The result may be affected by the sample size (50 vs 51), different clinical characteristics in the two groups  and selection bias. Meanwhile, it may be also explained by the lower effectiveness of non-cephalosporins/carbapenems drugs in the treatment of CnSPA BSI. Further studies should focus on the treatment of CnSPA.Previous studies found that appropriate therapy, no matter whether that be monotherapy or combination therapy, led to a significant reduction in mortality of patients with PA infections . A meta-tropenia . Howevertropenia , 40. Comtropenia . HoweverThe study has several limitations. First, it was retrospective in nature; therefore, it may be subject to selection bias and treatment options over the 10 entire years may be changeable . Second, as the large number of variables collected and the potential effects of residual confounding, some variables may be significant by chance alone. Third, it was a single center study containing little data; therefore, the results may not be applicable to other hospitals. Indeed, it is essential to evaluate the strains prevalent locally and the condition of the patients before selecting the optimal dosage regimen. In addition, we did not include adverse events, cost, and repeated infections in our analysis of risk factors for mortality.We found that pulmonary disease and exposure to carbapenems were independent risk factors for developing CnSPA BSIs. Appropriate therapy and prompt therapy reduced mortality rates. However, combination therapy was no better than monotherapy for reducing mortality associated with PA BSI. Combination therapy with β-lactams was as effective as carbapenems for treatment of PA BSIs.Additional file 1:Figure S1. Flowchart of the case selection process. (PDF 55 kb)Additional file 2:Figure S2. Annual incidence of PA bloodstream infections (PA and CnSPA) in hospital and ICU: 2007–2016. (PDF 40 kb)Additional file 3:Figure S3. Annual incidence of Pseudomonas aeruginosa bloodstream infections (PA and CnSPA): 2007–2016. (PDF 92 kb)Additional file 4:Table S1. Risk factors associated with 30 day mortality in patients with CnSPA BSIs. Table S2. Risk factors associated with 30 day mortality in patients with CSPA BSIs. Table S3. Clinical characteristics, infection status, and outcomes of patients with PA BSI who received definitive therapy. Table S4. Microbial susceptibility to piperacillin/tazobactam (PDF 100 kb)


There is growing evidence that alternative splicing (AS) plays an important role in cancer development. However, a comprehensive analysis of AS signatures in kidney renal clear cell carcinoma (KIRC) is lacking and urgently needed. It remains unclear whether AS acts as diagnostic biomarkers in predicting the prognosis of KIRC patients. In the work, gene expression and clinical data of KIRC were obtained from The Cancer Genome Atlas (TCGA), and profiles of AS events were downloaded from the SpliceSeq database. The RNA sequence/AS data and clinical information were integrated, and we conducted the Cox regression analysis to screen survival‐related AS events and messenger RNAs (mRNAs). Correlation between prognostic AS events and gene expression were analyzed using the Pearson correlation coefficient. Protein‐protein interaction analysis was conducted for the prognostic AS‐related genes, and a potential regulatory network was built using Cytoscape (version 3.6.1). Meanwhile, functional enrichment analysis was conducted. A prognostic risk score model is then established based on seven hub genes  that have high performance in the risk classification of KIRC patients. A total 46,415 AS events including 10,601 genes in 537 patients with KIRC were identified. In univariate Cox regression analysis, 13,362 survival associated AS events and 8,694 survival‐specific mRNAs were detected. Common 3,105 genes were screen by overlapping 13,362 survival associated AS events and 8,694 survival‐specific mRNAs. The Pearson correlation analysis suggested that 13 genes were significantly correlated with AS events (Pearson correlation coefficient >0.8 or <−0.8). Then, We conducted multivariate Cox regression analyses to select the potential prognostic AS genes. Seven genes were identified to be significantly related to OS. A prognostic model based on seven genes was constructed. The area under the ROC curve was 0.767. In the current study, a robust prognostic prediction model was constructed for KIRC patients, and the findings revealed that the AS events could act as potential prognostic biomarkers for KIRC. Our results provide the basis for further investigations into the pathomechanisms of KIRC and selection of the potential biomarkers for the early diagnosis of KIRC.22.1https://tcga‐data.nci.nih.gov/tcga/). In addition, we collected data of AS events from the TCGA SpliceSep (https://bioinformatics.mdanderson.org/TCGASplice‐Seq/). The percent splicing (PSI) values ranging from 0 to 1 are typically used to quantify AS events  from The Cancer Genome Atlas (TCGA) data portal of the KIRC cohort (The RNA‐Seq expression datasets were downloaded and then transformed from Fragments PerKilobase Million (FPKM) data into Transcripts PerKilobase Million (TPM) data. Using GRCh38.p2 annotation information provided by GENCODE, Ensemble ID was transformed into gene symbol, and the encoded protein gene was obtained. Finally, 605 samples with AS and RNA‐Seq data were included in the study, and 19,814 genes were obtained. The flowchart of the model building is shown in Figure 2.2There are seven types of AS events, including retained intron (RI), exon skip (ES), alternate promoter (AP), mutually exclusive exons (ME), alternate donor site (AD), alternate terminator (AT), and alternate acceptor site (AA). We analyzed the distribution of protein‐coding genes in seven types of AS events in KIRC. A visualization plot for AS events is shown in Figure 2.3p < .05 were determined using univariate Cox regression analysis. The distribution of the survival‐specific AS events/mRNAs was visualized in Figure Survival‐related AS events/mRNAs with 2.4When dealing with five or more groups, the Upset diagram was generated by the UpSetR package (version 1.3.3) . We used a combination of gene expression levels weighted by regression coefficient (β) originating from the multivariate Cox regression analysis to construct a risk score model. The formula for estimating the risk score for each patient is as follows: Risk score = β33.1The profile of AS events/genes for 487 patients from TCGA KIRC cohort was analyzed. After analyzing raw data, 46,415 AS events were detected, including 235 ME in 229 genes, and 2,831 RI in 1,904 genes, 3,720 AD in 2,302 genes, 3,872 AA in 2,685 genes, 8,632 AT in 3,772 genes, 9,509 AP in 3,807 genes, and 18,117 ES in 6,917 genes  >0.6, and AD had the highest performance in the risk classification of KIRC patients (AUC: 0.810–0.826) Figure .3.3A protein‐protein interaction network was constructed, and gene interaction networks of prognostic seven types of AS events were generated by Cytoscape Figure . The Gen3.4p < .01) and mapped to a String database with a score >0.4. The interactions among these genes were obtained. Visualization using Cytoscape is presented in Figure To explore the interactions among prognostic genes in seven types of AS events, the most significant prognostic genes were selected  were identified from the Cox multivariate analysis Table .To construct and validate the prognostic prediction model for KIRC patients, the seven characteristic genes were used to construct a multifactor survival model and to classify the prognosis in combination with the expression matrix. The results demonstrated that the seven genes had a good prognostic classification power in both datasets, and the AUC was high, suggesting that these genes may serve as prognostic markers for KC Figure .4AS plays an indispensable role in the modiﬁcation of mRNA isoforms, and it permits cells to produce a variety of mRNA and protein isoforms with multiple functions. AS is also responsible for producing biodiversity  were identified from the interaction network and correlation analysis between AS event and gene expression. Many of these genes were involved in the development of cancer. From the multivariate analysis for survival, the seven genes may be used to become biomarkers in classification for KIRC prognosis at AS events and gene expression levels.The authors declare that there is no conflict of interests.JKS, DBY, JGZ, and FS wrote the main manuscript text. JKS and YDL prepared Figures