The meaning of gene therapy is the delivery of DNA or RNA to cells for the treatment or prevention of genetic disorders. The success rate of gene therapy depends on the progression and safe gene delivery system. The vectors available for gene therapy are divided into viral and non-viral systems. Viral vectors cause higher transmission efficiency and long gene expression, but they have major problems, such as immunogenicity, carcinogenicity, the inability to transfer large size genes and high costs. Non-viral gene transfer vectors have attracted more attention because they exhibit less toxicity and the ability to transfer large size genes. However, the clinical application of non-viral methods still faces some limitations, including low transmission efficiency and poor gene expression. In recent years, numerous methods and gene-carriers have been developed to improve gene transfer efficiency. The use of Polyethylenimine (PEI) based transfer of collaboration may create a new way of treating diseases and the combination of chemotherapy and gene therapy. The purpose of this paper is to introduce the PEI as an appropriate vector for the effective gene delivery. A wide field of gene therapy is committed to a number of innovative treatments, which is likely to play an important role in preventing cancer deaths. The success of gene therapy depends on the development of a safe and effective gene delivery system . Different methods for gene therapy of cancer using different gene transfer vectors have been studied . In gene2.There are currently few attempts to review the current status and the needs of related research. The purpose of this article is to compensate for this shortage by reviewing recent developments and the challenges of PEI in vivo. For this purpose, related articles have been taken on web of science and pubMed sites, and out of 470 applied papers, 35 recent in vivo studies have been selected for further analysis. It is hoped that this article will create new insights and clinical efforts . Over th3.3.1.Cationic polymers have attracted great attention in recent years as non-viral vectors in gene delivery due to high cellular uptake efficiency, good water solubility, excellent transferability and easy synthesis. These polymers also have a high potential for drug delivery, which are due to their structure, which is appropriate for the biological process and can easily control the biodistribution and biocompatibility of carrier molecules. Cationic polymers due to their easy synthesis and low cost modification, can be effectively assemble with siRNA through electrostatic interaction and this positively charged condensed complex can improve cellular uptake and siRNA-mediated gene-silencing .3.2.Cationic polymers can be referred to positively charged macromolecules that can be inherently present in the polymer backbone or in the side chains. Most cationic polymers have primary, secondary or tertiary amine functional groups that can be protonated. They are also very different in the polymer structure  and can be different by placing positive charges (backbone or side chains) .10.1080/4.4.1.PEI is a cationic polymer used for many years in typical processes such as paper production, shampoo production, and water purification . HoweverPolymer chemistry has new things by business manufacturers, they produce poly(2-ethyl-2-oxazoline) with trade name Aquasolo. In addition, PEI has recently released a high degree of purity for Aquasolo, which is formed from 2-ethyl-2-oxazoline (>99.5% by GC) under compression conditions . On the In 2016, Itsuno, K. et al., studied low molecular weight branched PEI, linked to linear DNA (600 Da PEI). In this study, it has been shown that separation between heat of binding and heat of condensation is required and the excluded site model should be used for the PEI binding stage in the Isothermal Titration Calorimetry analysis (ITC). They performed the same ITC tests using PEI 25 kDa instead of 600 Da PEI. This means that a large PEI can attach to DNA multivalently, while the small PEI can be linked monovalently . The stuIn 2013, DeLuca et al. studied on layer composition of ferrocene-modified polyethyleneimine redox polymer films. The significance of these results is due to the first report of the use of the Fc-C6-LPEI redox polymer to improve the success of layer-to-layer composites. The electrochemical reaction obtained with Fc-C6-LPEI/GOX films shows that this redox polymer and layer-to-layer technique can be used for bio-sensor and biofuel applications. Additional applications with enzymatic systems can be the results of the success of multiple anionic polyelectrolytes . In 20104.1.1.+ ions, it shows weak buffer properties, which are critical to its use as a DNA delivery agent. It protects the DNA from the acidic environment of cell-uptake vesicles and guarantees release of DNA to the cytoplasm [2 replacement, polyethylenimine-1,2-cyclohexanedicarboxylic anhydride (PEI-CCA) and folic-polyethylenimine-1,2-cyclohexanedicarboxylic anhydride (FA-PEI-CCA). PEI-CCA and FA-PEI-CCA have significantly less cytotoxicity and have better blood compatibility than PEI, also have the undifferentiated ability to compress DNA [Cationic vectors are ideal candidates for gene delivery due to their ability to transfer large genes and scalable production . The synytoplasm . PEI/DNAytoplasm . In 2017ress DNA . In 2013ress DNA . Wang etIn 2017, drug delivery and the effectiveness of BMPPEI complex-conjugated with the foreign DNAs (BPDs) in promoting the testes-mediated gene transfer (TMGT) in mice were studied and the BPDs were compared with the liposome-conjugated foreign DNAs. The results showed that BPD clusters successfully reached cytoplasm and spermatogenesis cell nucleus through the injection test and expressed in the testicle of the transgene founder mice . In 20172 cells compared to PEI/pDNA complex [In 2016, Lazarus et al., reported the synthesis of PEI-coated gold nanoparticles for use as non-viral gene carriers. The results showed that the Au-PEI/pDNA complex increased 12-fold in HEK293 cells and increased 9-fold in HepG complex .4.1.2.The transfusion efficiency is closely related to the PEI binding with DNA and the ability to overcome a specific barrier . Traffic5.5.1.The delivered gene and the gene carrier determine the non-viral gene delivery strategies . Tissue 5.2.Recently, several delivery systems based on PEI development for cancer treatment have been introduced . NanocarIn this study, we present a summary of the design concepts and recent advances for improving drug delivery and gene delivery in vivo and in vitro. These multi-purpose biodegradable nanosystems are ultimately used for cancer chemotherapy and gene therapy .6.Recently, non-viral vectors, which are highly efficient, have been developed by modifying low molecular weight (600 Da) with a variety of functional groups . BecauseIn 2016, Zhang et al. studied low molecular weight PEI-based vectors with acid-labile ortho ester linkage to enhance the gene delivery. Results showed the improvement of the endosomal process of polyplexes and the reduction of toxicity of the substance after transfusion (post-transfection) . A studyIn vitro luciferase analysis shows that CS-PEI-Arg has better transfection efficiency than CS-PEI, which is superior to PEI. The results indicate that CS-PEI-Arg is a prominent candidate for gene delivery and can be used to treat liver or kidney diseases .In 2017, Chen and his coworker developed a biocompatible cationic pullulan-g-desoxycholic acid-g-PEI micelles with average diameter of 160.8 nm and zeta potential of about 28 mV for drug and gene collaboration for cancer therapy (MCF −7). These results showed that the use of a new amphiphilic bifunctional pullulan derivative (named as PDP) micelles is appropriate for effectively co-delivering functional gene and chemotherapeutic agent, which improve the efficacy of antitumor and systemic toxicity and good blood compatibility and low cytotoxicity in the hemolysis . In 2016Very unstable and cerium borohydride reducing reagent which is flammable in the environment may become stable through placing it on a polymeric substrate called polyethylenimine; then, this mild and new reducing reagent which is stable and could be kept for months in laboratory environment may be used in many organic synthetic reactions.Given the large size and the negative charge of nucleic acid, chemical modification of inorganic nanoparticles with functional groups or polymers is generally needed. Positively charged functional groups  or polymers, such as amino silane, polyethyleneimine (PEI), polyamidoamine (PAMAM), chitosan, are usually be employed to treat the nanoparticles before binding with DNA. For instance, PEI grafted GO exhibited enhanced chemotherapy efficacy towards HeLa cells by sequential delivery of anticancer drugs and siRNA , 82 Alde7.Gene therapy is capable of treating human diseases caused by defective genes and its purpose is to transfer genetic material to specific cells for the treatment of the disease. Protecting DNA against temperature and pH changes, and the destruction of lysosomes and passing through the membrane to target it are the abilities of the gene as a clinical treatment, which is strongly dependent on the use of appropriate gene directory. Today, all gene delivery carriers have been developed, such as several viral and non-viral vectors, has been improved and used to successfully cure some diseases. In general, both viral and non-viral vectors, despite the advantages and disadvantages, are used in recent advances in gene therapy strategies somewhat bring the expectations of years of gene therapy closer to reality and the hope of achieving more success. It seems that the ultimate gene therapy solution for treating many diseases in this century is human. The result of a great deal of research on this subject in recent years is very promising, and polyethylene imine can be used as an appropriate vector.


Resistance of gram-negative bacilli to carbapenems is rapidly emerging worldwide. In 2016, the World Health Organization defined the hospital-built environment as a core component of infection prevention and control programs. The hospital-built environment has recently been reported as a source for outbreaks and sporadic transmission events of carbapenemase-producing gram-negative bacilli from the environment to patients.Pseudomonas aeruginosa in a carbapenemase-low endemic setting.To assess risk after the identification of an unexpected, severe, and lethal hospital-acquired infection caused by carbapenemase-producing A case series study in which a risk assessment was performed on all 11 patients admitted to the combined cardiothoracic surgery and pulmonary diseases ward and the hospital-built environment in the Radboud University Medical Center, the Netherlands, in February 2018.P aeruginosa.Water and aerosols containing carbapenemase-producing  P aeruginosa.Colonization and/or infection of patients and/or contamination of the environment after the detection of 1 patient infected with carbapenemase-producing (VIM) P aeruginosa was unexpectedly detected in a man in his early 60s, who had undergone a left-sided pneumonectomy and adjuvant radiotherapy. No additional cases (colonization or infection) of carbapenemase-producing (VIM) P aeruginosa were detected. Plausible transmission of carbapenemase-producing P aeruginosa from the hospital environment to the patient via the air was confirmed by whole-genome sequencing, which proved the relation of Pseudomonas strains from the patient, the shower drains in 8 patient rooms, 1 sink, and an air sample.A total of 5 men  and 6 women  were admitted to the combined cardiothoracic surgery and pulmonary diseases ward. The risk assessment was performed after carbapenemase-producing (VIM) This study suggests that rethinking the hospital-built environment, including shower drains and the sewage system, will be crucial for the prevention of severe and potential lethal hospital-acquired infections. Pseudomonas aeruginosa in a carbapenemase-low endemic setting in the Netherlands.This case series study assesses risk after the identification of an unexpected, severe, and lethal hospital-acquired infection caused by carbapenemase-producing  To what extent does the hospital-built environment contribute to the transmission of carbapenemase-producing gram-negative bacilli?Pseudomonas aeruginosa. All identified sites were drained to 1 collection sewage point, likely resulting in airborne transmission originating from shower drains plus extensive contamination of water sources  in the hospital-built environment.In this case series study of 11 patients, a clustered localization of 8 shower drains, 1 sink, a positive air sample, and 1 patient were colonized and infected with carbapenemase-producing  Rethinking the hospital-built environment, including details such as shower drains and the sewage system, will be crucial for the prevention of severe and potential lethal hospital-acquired infections. Drain sampling (sinks and shower drains) was performed by inserting the E-Swab (BD) into drain holes. Environmental air sampling (1000 L) was performed using MAS-100 Eco (Lighthouse Worldwide Solutions) directly after the shower had run for 10 minutes. The air sampler was placed on the ground in the middle of the bathroom. Air sampling was repeated 15 minutes after the shower was turned off. All cultures were screened for carbapenemase-producing microorganisms following standard operating procedures by phenotypic analysis (carbapenem inactivation method) and genotypic analysis of all P aeruginosa isolates with an E-test for meropenem greater than 2 mg/L.14 The screening of patients and environmental sampling was conducted as part of a routine outbreak investigation and therefore no institutional review board approval was requested. Patients underwent screening after oral consent was obtained. Written informed consent was obtained from the relatives of the deceased patient. The article is in line with the guidance provided in the appropriate use and reporting of uncontrolled case series in the medical literature.15After the identification of a patient who was unexpectedly colonized with a highly resistant microorganism, fellow patients were screened according to Dutch national guidelines.Cleaning and disinfection of environmental surfaces of the patient room (bathroom included) was performed by daily cleaning of all surfaces plus disinfection of all high-touch surfaces using Bacillol 30 (Hartman) and Terralin (Schülke & Mayr Benelux). Terminal cleaning and disinfection of all surfaces including the bathroom was performed in case of patient transfer or discharge. Chlorine 0.1% solutions were used to disinfect the stainless steel shower drains and sink drains after mechanical cleaning with a brush.16 and an in-house python script. Read coverage was calculated as the total amount of sequenced nucleotides after filtering divided by the length of the reference genome, P aeruginosa Carb01 63 (RefSeq:NZ_CP011317.1). Samples with coverage less than 20× were omitted for further analyses. SPAdes, version 3.10.1,17 was used to assemble reads to contigs. Multilocus sequence typing types were derived from the contigs using multilocus sequence typing, version 2.5 (https://github.com/tseemann/mlst). Resistance genes were detected by using Abricate (https://github.com/tseemann/abricate) with database Resfinder.18 To obtain core single-nucleotide polymorphisms (SNPs), defined as SNPs that are shared among all strains, all samples including a reference set of 10 P aeruginosa strains were analyzed using kSNP, version 3.021.19 Minimal Spanning Tree was created using Kruskal’s algorithm.20 The Radboudumc Service department performed detailed mapping of the sewage systems in the pulmonary and thoracic surgery department.A sequencing library was constructed by using 2- to 5-ng genomic DNA as input for the Nextera XT DNA Library Preparation Kit (Illumina), and paired-end reads of 2 × 150 base pairs were generated using the Illumina NextSeq 500 (Illumina). Reads were filtered and cleaned by applying Trim galore, version 0.4.1,P aeruginosa in a man in his early 60s who had undergone a left-sided pneumonectomy and adjuvant radiotherapy. The patient had received a diagnosis of a pT3N2M0 adenoid cystic carcinoma 29 years prior to admission and was referred to our surgical unit because of a locoregional recurrence in his chest wall. After resection of the dorsal parts of ribs 9, 10, and 11, the patient developed a wound infection, resulting in a fistula to the residual pleural cavity. A Clagett open-window thoracostomy was performed to obtain adequate drainage of the cavity, which was surrounded by heavily calcified fibrous scar tissue. Shortly after the open window was created, the cavity became infected with multidrug-resistant P aeruginosa. A wide antibiotic multiresistance profile was observed, with resistance to meropenem, gentamicin sulfate, tobramycin sulfate, and ciprofloxacin hydrochloride and variable activity for ceftazidime sodium and amikacin sulfate. Only piperacillin sodium-tazobactam sodium and colistin sulfate displayed valuable activity against the isolated multidrug-resistant P aeruginosa. Antibiotic regimens consisted of combinations with piperacillin-tazobactam, ceftazidime, colistin, and amikacin in combination with local application of acetic acid by packed gauzes that were changed daily. However, the infection persisted, finally leading to an erosion and bleeding from the descending aorta. The aorta was inaccessible for surgical repair and, after the patient was stabilized, a thoracic endovascular aortic repair was performed, covering the defect by means of a stent. However, after 3 days, the patient developed recurrent bleeding, originating from the aorta proximal to the thoracic endovascular aortic repair stent. Extending the thoracic endovascular aortic repair stent was considered, but the patient refused further treatment and died the same day. More important, no risk factors for the carriage of carbapenemase-producing microorganisms  could be identified in our patient, which made us consider alternative routes of transmission of the P aeruginosa from other patients or the environment.In February 2018, we unexpectedly detected carbapenemase-producing  P aeruginosa resulted in screening for colonization in all 11 hospitalized patients admitted to the same ward. Following national guidelines, we initiated the screening of all admitted patients in the same ward at risk for colonization with carbapenemase-producing gram-negative bacilli. All P aeruginosa isolates in the ward were analyzed for carbapenemase production. No additional cases (colonization or infection) were detected. Following the national guidelines, no health care professionals were screened for multidrug-resistant gram-negative bacilli. Thorax, urine, and blood cultures obtained in the 7 months between the initial patient’s left-sided pneumonectomy and the open-window thoracostomy were evaluated for the presence of P aeruginosa. During this period, 10 wound cultures were obtained, of which 2 wound cultures were positive for Staphylococcus epidermidis and Propionibacterium acnes; in addition, 1 urine culture was positive for Citrobacter koseri. None of the cultures was positive for P aeruginosa. In the absence of other patients with positive cultures for P aeruginosa and with the knowledge that the patient’s cultures were negative prior to the Clagett open-window thoracostomy, we initiated environmental screening focusing on moist areas of rooms in which our patient had been hospitalized.The unexpected finding of a patient with carbapenemase-producing P aeruginosa from a shower drain in the patient’s room, the environmental sampling was extended to the entire ward. One sink that had a negative result for P aeruginosa in the first screening had a positive result in the second screening 2 weeks later. After evaluation of the first positive environmental samples we decided to investigate possible airborne transmission from the shower drains by collecting air samples directly after the shower had run for 10 minutes and 15 minutes after the shower had been turned off.For efficiency reasons we conducted environmental sampling in a stepwise approach. In the entire workup we conducted 4 rounds of screening of environmental surfaces  were found in other air samples after the showers in the initial room and 7 other patient rooms had run. Transmission of carbapenemase-producing P aeruginosa between the patient, the air sample, and the hospital environment was confirmed by whole-genome sequencing  in comparison with reference strains. A schematic overview of the ward layout shows the clustered localization of the shower drains with positive results for P aeruginosa in relation to the collection sewage point  and the P aeruginosa was cultured 4 months earlier and never thereafter. We could not detect the initial source for this transmission event; it is unlikely the patient who initially underwent a left-sided pneumonectomy and adjuvant radiotherapy could have been the index patient owing to the thorax, urine, and blood cultures negative for P aeruginosa that were obtained in the period between the left-sided pneumonectomy and the open-window thoracostomy. Furthermore, soon after the initial identification of our patient, we confirmed that the shower drains of 7 additional patient rooms were positive for P aeruginosa by whole-genome sequencing. It seems unlikely that the carbapenemase-producing P aeruginosa could have migrated through biofilms to the other patient rooms in the time between the first positive patient culture and the positive environmental samples. Hand hygiene compliance in the affected ward is routinely measured since the introduction of a hospital hand hygiene campaign 4 years ago and is currently high (80% compliance for the 5 moments of hand hygiene according the WHO). Also, no other surfaces that came into contact with the pleural cavity of the patient (accessed by Clagett open-window thoracostomy) tested positive for P aeruginosa. Last, our patient had no known risk factors for colonization with a carbapenemase-producing microorganism.This investigation was conducted to explain an unexpected carbapenemase-producing P aeruginosa. No environmental cultures were available prior to the first positive patient culture. Furthermore, we provide data from only 1 hospital; more evidence is needed from other contexts in both high- and low-resource settings.Some limitations of this study need to be addressed. First and most important, this is a risk assessment after 1 severe case with carbapenemase-producing P aeruginosa but also trials to determine clinical and environmental benefits of plumbing (shower and sink) changes or changing technology such as novel sink drains that reduce splashing.Given the substantial effect of infections with carbapenem-producing gram-negative bacilli on the clinical outcome of patients with open wounds, appropriate measures should be taken to reduce the risk of airborne transmission of gram-negative bacilli to open wounds during and after showering. Interventions should focus primarily on hardware (new engineering solutions for showers and plumbing systems). We advise the development of new regulations and guidelines that formalize the management of sinks, showers, and sewage systems in hospitals and should prescribe a number of specific requirements. These new guidelines should be in line with guidelines that aim to prevent health care–acquired legionnaires’ disease. We recommend further studies to confirm the spread of


To investigate the heterogeneous enhancement pattern in normal lymph nodes of healthy mice by different albumin-binding contrast agents.  The enhancement of normal lymph nodes was assessed in mice by dynamic contrast-enhanced MRI (DCE-MRI) after the administration of two contrast agents characterized by different albumin-binding properties: gadopentetate dimeglumine (Gd-DTPA) and gadobenate dimeglumine (Gd-BOPTA). To take into account potential heterogeneities of the contrast uptake in the lymph nodes, k-means cluster analysis was performed on DCE-MRI data. Cluster spatial distribution was visually assessed. Statistical comparison among clusters and contrast agents was performed on semiquantitative parameters  and on the relative size of the segmented clusters. p < 0.01) and wash-in (p < 0.05) rates were greater in the inner cluster, which also showed a steeper wash-out rate than the outer cluster . The size of the outer cluster was greater than that of the inner cluster by Gd-DTPA (p < 0.05) and Gd-BOPTA (p < 0.01). The enhancement pattern of Gd-DTPA was not significantly different from the enhancement pattern of Gd-BOPTA.  Cluster analysis of DCE-MRI data revealed at least two main clusters, localized in the outer portion and in the inner portion of each lymph node. With both contrast agents, AUC ( DCE-MRI in normal lymph nodes shows a characteristic heterogeneous pattern, discriminating the periphery and the central portion of the lymph nodes. Such a pattern deserves to be investigated as a diagnostic marker for lymph node staging. Dynamic contrast-enhanced MRI (DCE-MRI) has been widely used to quantify tissue perfusion in preclinical , 2 and cThanks to high-resolution T1-weighted images, DCE-MRI has been extensively applied in clinical studies to characterize the breast  and soliThe overarching aim of our study is to define the diagnostic potential of DCE-MRI for lymph node staging. For this purpose, the first step is investigation of normal lymph nodes since the definition of the enhancement pattern of normal nodal tissue is a needed preparatory knowledge to reliably detect alterations induced by metastasization. The aim of the present study is therefore obtaining the definition of the enhancement pattern in DCE-MRI of normal lymph nodes through systematic investigation in healthy mice. A further aim is to develop a semiautomatic and operator-independent image analysis procedure by using cluster analysis of DCE-MRI enhancement patterns.Moreover, Gd-based contrast agents can have different binding properties to albumin and consequently different capability to reveal blood vessels , 22, pot2 and O2 containing 0.5–1% isoflurane  and were cannulated in the tail vein for contrast agent injection during DCE-MRI scan. A single birdcage coil (3.5 cm i.d.) configuration was used for radiofrequency excitation and MRI signal detection. Images were acquired using a BioSpec tomograph  equipped with a 4.7 T, 33 cm bore horizontal magnet . For the imaging session, mice were placed in a prone position over a heated bed; body temperature and respiratory rate were monitored by using an MRI-compatible physiological monitor .Athymic nude mice were anesthetized by inhalation of a mixture of N2, slice thickness: 0.5 mm, number of averages: 8, and RARE factor: 8) was applied to investigate the presence of a fatty hilum, which has been often reported in human lymph nodes [Before the administration of the contrast agent, a standard non-fat-suppressed T1-weighted sequence  during the time interval between the third and fourth scan of the dynamic series: (i) Gd-DTPA and (ii) Gd-BOPTA.Afterwards, a dynamic series of multislice T1-weighted RARE images were acquired with fat suppression and with the following parameters: TR/TE: 550/7.6 ms, flip angle: 180°, matrix size: 175 × 100, number of slices: 6, field-of-view: 3.5 × 2.0 mmDCE-MRI was performed in total on 9 healthy mice (5 mice were injected by Gd-DTPA and 4 by Gd-BOPTA).The experimental plan received authorization from the Italian Ministry of Health  and was approved by the Animal Care and Use Committee of the University of Verona. Animal work was conducted following the Italian law (D.L. no. 26 of 4 March 2014) and the European Union normative (2010/63/EU). Major efforts were performed to minimize the number of animals and to avoid their suffering.nd volume after the contrast agent injection was used as a reference image for the registration of the whole time series. When the linear registration approach was not sufficient, a nonlinear approach was adopted, carrying out nonlinear registration by the FNIRT tool of FLS and finely tuning the registration parameters to obtain a “gentle” warp field.Some DCE-MRI scans were affected by peristalsis and breath-induced motion. To compensate for these displacements, a linear registration approach was adopted by means of the MCFLIRT tool of FSL . Even thPRE) from the signal intensity at a given time point SI(t) and normalizing it by (DEMAX)MUSCLE, that is, the maximal differential enhancement over an area drawn on the tight muscle:The subsequent postprocessing was performed by MATLAB . For each node, normalized differential enhancement (NDE) curves were calculated on a pixel-by-pixel basis, subtracting the signal intensity before contrast injection  was chosen to detect potential heterogeneities. To verify whether this arbitrary choice could be appropriate, principal component analysis (PCA) was performed on the same set of NDE curves, to obtain the data variance explanation as a function of the number of components.Segmented colour-coded maps were obtained for each lymph node, to visualize the spatial distribution of each cluster obtained by cluster analysis.After cluster analysis, in each lymph node, the NDE curves of each pixel belonging to a specific cluster were averaged to obtain the cluster-averaged NDE curves. Semiquantitative parameters were then extracted from these curves, namely, area under the curve (AUC), wash-in rate, and wash-out rate. The wash-in rate was defined as the maximum slope of the NDE curve between two consecutive time points comprised between the last baseline point and the point of maximal enhancement . The wasStatistical differences in the semiquantitative curve parameters (between clusters and between contrast agents) were assessed by two-way ANOVA, and the results were corrected for multiple comparisons with the Bonferroni method.μm thick sections were cut and stained with hematoxylin and eosin (H&E). The sections were observed using an optical microscope  at 4x and 10x magnifications.For histological investigation, lymph nodes were excised and fixed in 4% paraformaldehyde for four hours. After fixation and embedding in paraffin, 7 Only superficial inguinal lymph nodes, clearly visible on DCE-MRI, were considered. Due to motion induced by breathing and bowel peristalsis during the MRI acquisition, the registration procedure was applied in 9 nodes. In 2 cases, the linear registration approach was not sufficient, being the images affected by bowel motion really close to the node, and they required nonlinear correction. In one case, motion produced a very large shift that was not fully recovered by the motion correction procedure, and the lymph node was excluded from the successive analysis. In total, 15 nodes were successfully identified and included in the analysis (9 by Gd-DTPA and 6 by Gd-BOPTA). Representative fat-suppressed DCE-MRI images of a healthy node are reported in Figures Cluster analysis revealed a heterogeneous structure in the enhancement pattern of the lymph nodes. PCA performed on the NDE curves demonstrated that two main components were necessary and sufficient to explain at least 90% of the variance in all the 15 nodes . AdditioThe cluster-averaged NDE curves and the corresponding coloured segmented maps of all the 15 examined lymph nodes are shown in The parameters calculated on the cluster-averaged NDE curves are reported in p=0.056) with Gd-DTPA.Two-way ANOVA was applied to compare the semiquantitative perfusion parameters averaged over the two clusters (significant differences are reported in Two-way ANOVA performed through contrast agents revealed no statistically significant differences in the enhancement pattern of the two contrast agents tested here.Histological analysis performed with H&E staining confirmed a heterogeneous structure of the normal node Figures  and the In this study, cluster analysis was applied on DCE-MRI data acquired on normal nodes of healthy mice by two Gd-based contrast agents characterized by different albumin-binding properties. k-Means clustering was applied to identify potential heterogeneities, and the minimum number of clusters was utilized in the algorithm. Of note, PCA suggested that most of the variability of the lymph node contrast enhancement could be accounted for by two main components with both contrast agents. The applied clustering method was based only on the enhancement pattern and not on the spatial position of each pixel assigned to the cluster; that is, neighborhood connectivity was not considered by the algorithm.Of relevance, such a heterogeneous enhancement pattern arising from k-means evidenced a marked anatomical structure, regardless of the contrast agent used. In fact, the two clusters identified in each node resulted clearly localized in the outer portion and in the inner portion of the nodes, respectively. The observed pattern seems to be compatible with the functional organization of a normal lymph node, composed of two main functional units, the cortex and the medulla. Since the lymphatic flow is directed from the capsule and the cortex of the lymph node towards the medulla and the hilum, in this latter portion the contrast agents might accumulate also because of interstitial diffusion, at least partially explaining the greater contrast uptake in the inner region of the lymph nodes.The observed spatial pattern characterized the heterogeneous distribution of the enhancement in all the assessed lymph nodes. Independently from the contrast agent used, AUC and wash-in rate were greater in the inner cluster, which also showed a steeper wash-out rate than the outer cluster both with Gd-BOPTA and by Gd-DTPA. On the contrary, the enhancement of Gd-DTPA was not significantly different from the enhancement pattern of Gd-BOPTA.Many studies investigated the role of postcontrast T1 imaging in assessing the lymph node status, including quantitative assessment on DCE-MRI, but to our knowledge, the peculiar heterogeneity of contrast enhancement in normal nodes has not been reported before. To the best of our knowledge, only one study focused on normal nodes, analysing axillary lymph nodes in breast cancer patients . HoweverInterestingly, in a study aiming at classifying axillary lymph nodes in breast cancer patients , the besIt is worth noting that the identification of a normal enhancement pattern might have a role in the detection of possible alterations induced by the metastatic transformation. For example, the accuracy obtained by lymphotropic iron oxide nanoparticles for nodal staging , 30 was In conclusion, the results obtained showed a heterogeneous pattern of enhancement in normal lymph nodes, independently of the contrast agent used. Semiautomatic cluster analysis of signal intensity vs. time data showed the existence of two clusters characterized by different signal intensity dynamics belonging to the inner and outer regions of lymph nodes.This heterogeneous pattern might be peculiar of normal lymph nodes and, if confirmed on human lymph nodes, should be deeply investigated to assess any alteration possibly induced by the metastatic transformation and, consequently, its potential role for nodal staging.


ALMS1 gene and characterised by childhood onset obesity, dyslipidaemia, advanced non-alcoholic fatty liver disease, diabetes and extreme insulin resistance. There is evidence of multi-organ fibrosis in ALMS and severity of the disease often leads to organ failure with associated morbidities, resulting in reduced life expectancy. There are no specific treatments for this disease, and current management consists of only symptomatic therapies. PBI-4050 is a new molecular entity with demonstrated anti-inflammatory and anti-fibrotic activities in preclinical models, including animal models of human diseases characterized by progressive fibrosis in the kidney, heart, liver and lungs. Moreover, completed Phase 2 studies in type 2 diabetes mellitus with metabolic syndrome and idiopathic pulmonary fibrosis further support the anti-inflammatory and anti-fibrotic activity of PBI-4050. Together, these data suggest that PBI-4050 has the potential to treat the pathological inflammatory and fibrotic features of ALMS. The aim of this study is to evaluate the safety and anti-inflammatory & anti-fibrotic activities of PBI-4050 in subjects with ALMS.Alström syndrome (ALMS) is a very rare autosomal recessive monogenic disorder caused by a mutation in the This is a Phase 2, single-centre, single-arm, open-label trial. A total of 18 patients with ALMS will be enrolled to receive PBI-4050 at a total daily oral dose of 800 mg for an initial 24 weeks with continuation for an additional 36 or 48 weeks. Standard assessments of safety include adverse events, clinical laboratory tests, vital signs, physical examination and electrocardiograms. Efficacy assessments include adipose tissue biopsy, hyperinsulinaemic-euglycaemic glucose clamp, adipose tissue microdialysis, liver transient elastography, liver and cardiac magnetic resonance imaging, and laboratory blood tests.This is the first clinical study of PBI-4050 in subjects with ALMS. Given the rarity and complexity of the disease, a single-centre, single-arm, open-label design has been chosen to maximise subject exposure and increase the likelihood of achieving our study endpoints. The results will provide valuable safety and preliminary evidence of the effects of PBI-4050 in ALMS, a rare heterogeneous disease associated with progressive fibrosis and premature mortality.NCT02739217, February 2016) and European Union Drug Regulating Authorities Clinical Trials .The trial is registered on ClinicalTrials.gov  contains supplementary material, which is available to authorized users. Alström syndrome (ALMS) is a rare autosomal recessive genetic disorder with an estimated prevalence of less than one per million . It is cALMS is caused by mutations in ALMS1, a large gene located on chromosome 2p13 with ubiquitous expression . In addidb/db mouse) to be effective in preventing the loss of insulin production that characterizes the natural history in these animals and leads to death from hyperglycaemia at 24 to 26 weeks of age -glucose (enriched to 4%) is commenced at time point 124 min. During the insulin-stimulated state period, blood sugars are checked every 5 min to allow for dextrose infusion rate adjustments to maintain fasting glycaemic levels. At time points 210, 225 and 240 min, steady state blood samples are collected. The rates of endogenous glucose production, glucose disposal and lipolysis  are calculated.Insulin  infusion is then started at 120 min at a rate of 40 mU/mSubject’s withdrawal of consent;An AE, which in the opinion of the investigator warrants discontinuation of treatment;Pregnancy;Death;Substantial protocol deviation;Investigator’s decision;Sponsor’s decision;Subject starting a prohibited therapy (see Section 5.6);aspartate transaminase or alanine transaminase rises to > 5 × upper limit of normal;A drop in heart rate from baseline by 15 beats per minute that is associated with clinically relevant cardiovascular symptoms as determined by the investigator;A drop in systolic blood pressure by 20 mmHg or diastolic blood pressure by 15 mmHg from baseline that is associated with clinically relevant cardiovascular symptoms as determined by the investigator.PBI-4050 will be permanently discontinued for the following reasons:Subjects who discontinue study treatment but have not withdrawn consent will be asked to attend the appropriate End-of-Treatment and End-of-Study visits, depending upon whether they withdraw before or after Week 24. Subjects who withdraw consent will not have further study-related information collected for the clinical trial database, with the exception of follow-up on on-going AEs or any new AEs within the safety follow-up period. Subjects who withdraw due to AEs will be followed until the event has resolved or stabilized.In the case of any substantial deviation from the protocol, the investigator and sponsor will decide on the further participation of the subject in this study, having discussed all relevant aspects. The sponsor may discontinue the study in its entirety before its completion for reasonable cause, provided that written notice to the investigator, regulatory authorities and independent ethics committee (EC) is submitted in reasonable time in advance of the intended termination.If subjects decide to enter the ALMS rollover study (Study PBI-4050-CT-9-10) after completing the 36- or 48-week extension period, then they will sign an informed consent for that study and stop participation in the current study.All SAEs will be reported to pharmacovigilance/safety personnel within 24 h after the investigator becomes aware of the event. All relevant information about any suspected unexpected serious adverse reaction (SUSAR) occurring during the course of a clinical trial and if fatal or life-threatening will be reported as soon as possible and in any event not later than 7 days to the competent authority. All SUSARs occurring in the interventional study will be entered into a European database established in accordance Directive 2001/20/EC and reported to the relevant ECs. A Data Safety Monitoring Board will review individual subject safety data in an on-going fashion. An unaffiliated clinical research associate will monitor the data collected throughout the study, thus providing quality control (QC) of the study and QC of the database and data management.p < 0.05. All statistical analyses will be made using observed data. No imputation will be made.This study is purely exploratory and aims to evaluate safety and tolerability of PBI-4050 and examine its effects on biomarkers. The study will collect data to derive descriptive statistics on secondary endpoints for future studies and no statistical hypothesis will be tested. A minimum of 8 subjects is deemed necessary in this part of the study. The data will be summarized using mean, standard deviation, median, and range. Demographic  and baseline characteristics will be presented descriptively at baseline. Categorical variables will be reported as numbers and percentages. Paired t-test or where appropriate the non-parametric equivalent (Wilcoxon signed-rank test) will be used to compare variables before and after intervention. The Shapiro-Wilk test will be used to test the normality of the distribution. In the event that the normality assumption fails at the 0.10 alpha level of significance, the Wilcoxon Signed-Rank test will be used instead. Absolute values and changes from baseline in safety laboratory tests will be summarized by visit over time and presented in shift tables. To evaluate the shift over time, a mixed model comparing the slope before baseline  to the slope after baseline (on-treatment data) will be used. For comparing results of repeated samples, for example adipose tissue microdialysis where there are multiple time points during the same test, repeated measures analysis of variance will be used. All analysis will be conducted using SPSS statistical software. The significance level for this study is set at ALMS is a rare genetic disease characterised by multiorgan dysfunction and progressive fibrosis, resulting in reduced life expectancy . Given iStudy PBI-4050-ATX-9-05 will initially evaluate the safety and tolerability of PBI-4050 over a 24-week period, during which therapeutic efficacy in terms of modification of the metabolic syndrome, liver and cardiac fibrosis and pro-inflammatory and pro-fibrotic state will be assessed, followed by an exploratory phase in those subjects who are tolerating therapy. Because of the complexity of the ALMS phenotype, a variety of investigations are incorporated into the study. This study is not intended as a full assessment of the safety and efficacy of PBI-4050. Rather, this study will provide valuable safety and biomarker evidence to support further development of PBI-4050 for the treatment of ALMS, a disease with severe morbidity and early mortality in which PBI-4050 has the potential to improve these outcomes.Recruitment to Study PBI-4050-ATX-9-05 began in February 2016. The study has recruited 12 subjects in the main study and 9 subjects in the extension phase. The study is currently recruiting in the UK and scheduled to end in 2018.Additional file 1:Schedule of Study Procedures (Main Study). Study Visits Initial 24 Weeks. Study Visits during the Initial 24 Weeks of Treatment. The schedule of study procedures for the enrolment, intervention, and assessments for participants is presented in detail in Additional file Additional file 2:Schedule of Study Procedures (Extension Period). Study Visits during Extension Period. Study Visits During the 36- or 48-Week Extension Period. The schedule of study procedures for the enrolment, intervention, and assessments for participants is presented in detail in Additional file Additional file 3:Exclusion criteria. This file list the exclusion criteria for the study. Subjects will not enter the study if any of the exclusion criteria listed in Additional file


The local climate zone (LCZ) scheme was originally proposed to provide an interdisciplinary taxonomy for urban heat island (UHI) studies. In recent years, the scheme has also become a starting point for the development of higher-level products, as the LCZ classes can help provide a generalized understanding of urban structures and land uses. LCZ mapping can therefore theoretically aid in fostering a better understanding of spatio-temporal dynamics of cities on a global scale. However, reliable LCZ maps are not yet available globally. As a first step toward automatic LCZ mapping, this work focuses on LCZ-derived land cover classification, using multi-seasonal Sentinel-2 images. We propose a recurrent residual network (Re-ResNet) architecture that is capable of learning a joint spectral-spatial-temporal feature representation within a unitized framework. To this end, a residual convolutional neural network (ResNet) and a recurrent neural network (RNN) are combined into one end-to-end architecture. The ResNet is able to learn rich spectral-spatial feature representations from single-seasonal imagery, while the RNN can effectively analyze temporal dependencies of multi-seasonal imagery. Cross validations were carried out on a diverse dataset covering seven distinct European cities, and a quantitative analysis of the experimental results revealed that the combined use of the multi-temporal information and Re-ResNet results in an improvement of approximately 7 percent points in overall accuracy. The proposed framework has the potential to produce consistent-quality urban land cover and LCZ maps on a large scale, to support scientific progress in fields such as urban geography and urban climatology. The 17 In addition to its strong usefulness in urban climate studies , the potCurrent large-scale LCZ mapping efforts are generally community-based projects that use freely available Landsat data and free software packages . The oveAnother promising approach is supervised automatic LCZ classification with satellite remote sensing images , which c•Comparable LCZ classification accuracies can be achieved using Sentinel-2 or Landsat-8 imagery; auxiliary data, such as OpenStreetMap (OSM), Global Urban Footprint (GUF), and VIIRS nighttime light, is not really necessary .•Compact mid-rise) tends to be falsely classified into LCZ 3 (Compact low-rise) and LCZ 1 (Compact high-rise).As a result of inter-class similarity and the class imbalance problem in reference dataset, it is difficult to differentiate building heights and distinguish similar LCZs using Sentinel-2 images alone . For exa•Compact high-rise and Compact mid-rise), a high weighted accuracy indicates that the urban super-class can be accurately distinguished from the natural classes.Despite of a relatively low LCZ mapping accuracy (with average accuracy of about 50%), a quite high weighted accuracy (95%) is achievable . As weigWithin this context, the primary goal of our study was to provide further insights into the methodological aspects of LCZ mapping from multi-seasonal earth observation data using deep learning based methods. This study is an extension of our previous work in which we applied a residual convolutional neural network (ResNet) without consideration of temporal information and published the following findings:Based on our previous results, we were motivated to derive a new, simplified land cover classification scheme containing 6 aggregated classes. The correspondence between these derived urban land cover classes and the original LCZs is shown in •Can land cover classification benefit from the temporal information contained in multi-seasonal Sentinel-2 images?•How can an appropriate network architecture capable of extracting spectral-spatial-temporal features be designed to improve the classification accuracy?•How can each LCZ benefit from the temporal information contained in multi-seasonal images?In this study, we focused solely on the freely available Sentinel-2 images , which pDense trees and Low plants . The temporal dependency can be modeled by either simply stacking multi-seasonal images or using a recurrent network, using an assumption under both modelling approaches that the spectral information for different land cover classes exhibits different patterns that change by season, which is obviously true for land cover classes such as w plants .The remainder of this paper is structured as follows. In Section 2When using multi-seasonal Sentinel-2 images as inputs for deep learning-based land cover classification, two approaches can be used to exploit temporal information. The first is to stack all images from different seasons as inputs of networks. The other is to treat multi-seasonal images as a changing representation of urban environments and to adapt state-of-the-art recurrent networks to model temporal dependencies of those images.The proposed recurrent residual network architecture (Re-ResNet) is illustrated in 2.1We use a ResNet in the proposed method because such structures have demonstrated their ability to outperform others in image recognition on several benchmark datasets, including the Street View House Numbers (SVHN) and ImageNet datasets . The speThe ResNet has a total of four residual blocks, each comprising three convolutional layers and one shortcut for bypassing two successive convolutional layers. Through the shortcut connection, the output of two stacked convolutional layers are added to the output of the first of the three convolutional layers. The convolutional layers have a rather small . In this study, an LSTM architecture was used to construct a recurrent sub-network in our Re-ResNet because such networks have proven to be a quite powerful tool for modeling temporal concepts .•The input gate •The forget gate •The output gate t, given an input W and b are the weight and bias terms, respectively. At season ee gates . The setAll of the networks are trained from scratch using the TensorFlow framework with a mini-batch size of 32. The Nesterov Adam  optimiza33.1The study areas were seven cities locating in central Europe: Paris, Amsterdam, Cologne, Munich, Milan, London, and Berlin.To fully validate the proposed approach, we designed a cross-validation experimental setup, which is illustrated in 3.2For each city, we used Google Earth Engine (GEE)  to creatWe used 10 of the 13 Sentinel-2 imagery bands: B2 (Blue), B3 (Green), B4 (Red), and B8 (Near-infrared) with a 10-m ground sampling distance (GSD); and B5 (Red Edge 1), B6 (Red Edge 2), B7 (Red Edge 3), B8a (Red Edge 4), B11 (Short-wavelength infrared 1), and B12 (Short-wavelength infrared 2) with a 20-m GSD, which were up-sampled to a 10-m GSD using cubic resampling. Bands B1 (Aerosols), B9 (Water vapor), and B10 (Cirrus) were not employed, as they mostly include information regarding the atmosphere and therefore have limited relevance to land cover differentiation. No additional extracted index measures or external auxiliary datasets were exploited, as our previous work revealed that they had limited contributions to deep learning-based methods .Lightweight low-rise), which primarily represents slums, isn’t existing in the study areas. The LCZ reference labels for the study areas were taken from the LCZ42 dataset , which w3.3Data augmentation was carried out for LCZs 1, 3, 9, 10, 2, 8, and G by performing horizontal and vertical flip and rotation. In addition, class 3, i.e., LCZ9, was oversampled by using its samples repeatedly, to balance the land cover samples. Finally, the LCZ classes were combined by applying the scheme shown in As this process resulted in a completely balanced set of test samples, only two measures had to be used for accuracy assessment: overall accuracy (OA) and kappa coefficient.3.4The classification results obtained using the respective approaches are listed in A detailed comparison of the applications of the respective approaches to the different test cases is shown in The contributions of temporal information by the respective individual land cover classes are shown in 3.5Sparsely built) is often misclassified as class 5 (Vegetation), class 2 (Open built-up area), and class 4 (Large low-rise and heavy industry).The class-wise classification accuracies of the Re-ResNet results for the seven experimental sets are listed in 3.6A zoomed-in view of the city center and a suburban area of Munich, Germany are shown in To illustrate the potential of Re-ResNet for large-scale LCZ mapping using a given number of reference LCZ samples, LCZ maps of three sample cities Munich, Berlin, and Milan are shown in 3.7To illustrate teh relative advantage achieved by using Re-ResNet over st_ResNet instead of st-ResNet, we graph the difference between the Re-ResNet and st-ResNet OA scores against number of training samples in We then carried out seven additional LCZ classification experiments in which st-ResNet and Re-ResNet were applied using different numbers of training samples. The improvement in averaged accuracy (AA) obtained by using Re-ResNet instead of st-ResNet is apparent in 4Both the classification accuracy and the produced land cover and LCZ maps in Section In light of these experimental results, the contribution of temporal information to the LCZ-derived land cover and LCZ classification and the comparative advantage of the proposed network will be discussed in this Section. Furthermore, the remaining challenges and possible solutions will be analyzed.4.1A comparison of the classification accuracies resulting from approaches with- and without considering temporal information in  reveals It is also seen from From 4.2The effect of the proposed network architecture is apparent from the improvement achieved relative to st-ResNet in terms of OA and Kappa, as indicated in Nevertheless, the accuracy of the Re-ResNet can be lower than that obtained from a single-season input, as is true in the case of London and Munich. This occurs as a result of the varying qualities of multi-seasonal images, as shown in 4.3Open built-up area), 3 (Sparsely built), and 4 (Vegetation), as these show clear changes over different seasons, but the improvements seen for Heavy industry, Compact built-up area, and Water motivate us to further investigate the learned features of Re-ResNet in future research.Sparsely built) was not accurately mapped by any of the approaches, including Re-ResNet. One reason is that this class can be easily and understandably misclassified as Open built-up area and Vegetation. Its accuracy can be potentially improved by adding more samples of class 3 to the training data or by resorting to complementary datasets. In addition, it is possible that some Sparsely built training samples actually contain no buildings, i.e., that they are noisy samples. This motivates us to try to develop robust approaches capable of dealing with label noise in an appropriate manner.In addition, as seen in 5The goal of this study was to contribute to the automatic mapping of large-scale LCZ-derived land cover with a given amount of reference data. In particular, we investigated transferability among different cities. For this, we proposed a novel recurrent residual network architecture, called Re-ResNet, that combines a residual convolutional neural network with a recurrent neural network. Re-ResNet is able to learn a joint spectral-spatial-temporal feature representation in a unified framework using multi-seasonal Sentinel-2 imagery as the network input. The method was validated over a large-scale study area spreading over seven central European cities, with the experimental results demonstrating that the proposed approach outperformed ResNet with single-seasonal images as inputs and st-ResNet with stacked multi-seasonal images as inputs. Systematic analysis based on the results also clearly revealed the effectiveness of using the temporal information contained in multi-seasonal, multi-spectral Sentinel-2 imagery for urban land cover classification.Even though we were able to demonstrate that the proposed Re-ResNet can generally improve classification accuracy, we anticipate a need for two further avenues of investigation and research: differentiating the Sparsely built class from the Open built-up area and Vegetation classes, and an application-driven analysis of the resulting maps. After solving these two problems, it should be possible to produce land cover and urban human settlement maps with even higher accuracy to provide more reliable morphological information on cities worldwide that can be used to obtain further knowledge and insight into the ongoing process of urbanization.


Measurements from four MEMS resonator geometries designed for ultrasensitive detection operating between 2-MHz and 8-MHz monolithically integrated with a low-noise CMOS capacitive readout circuit were analyzed and used to determine the resolution achieved in terms of displacement and capacitance variation. The CMOS-MEMS system provides unprecedented detection resolution of 11 yF·Hz Micro and nanoelectromechanical resonators have been extensively proposed and experimentally tested for sensing purposes in the biological and chemical domains ,2, amongsolution . In thisications . Such a progress . Both, trnatives ,9,10,11 rnatives ,13, beinrnatives ,15,16,17olutions ,15,16,17The MEMS resonators considered in this work were fabricated using the top metal layer (Aluminum) of a commercial 0.35-μm CMOS technology followed with a mask-less wet-etching post-CMOS step in our laboratory to release the mechanical moving parts  18]. Th. Th18]. 0.85 μm, determined by the technology layer used. The remaining structure dimensions constitute the design parameters referred to as (see bL), beam width (bW), platform length (pL), and platform width (pW) taking the values given in The structure thickness (t) was Once the resonators mechanical parameters are given, we provide the electrical ones, modeling the resonator as an RLC lumped equivalent circuit  with a p® program  , because of its high sensitivity to both temperature and humidity [The main goal of this work is to characterize the thermomechanical vibrations spectrum of the resonators with no driving force. For this purpose, the driving electrode was grounded and the output monitored using a spectrum analyzer while the data was recorded using a LabViewUSA) see . The noiG). Considering the parasitic input impedance  , and theT is the absolute temperature, The thermomechanical noise spectrum is shaped by the second order frequency response of the resonator  accordinT as far as Notice that Equation (14) only depends on The model predictions were experimentally confirmed for all the geometries thus corroborating the noise capabilities of these CMOS-MEMS devices. The thermomechanical noise was observed at 20 °C and bias voltages ranging from 40 V to 90 V both under ambient pressure  and vacurequency b.The experimental data shows that the frequency decreases as the bias voltage increases due to the well-known spring softening effect. Plate-B1 resonator exhibits the highest peak value  in agreeRM see . This beThe same behavior was found when operating the resonators under vacuum conditions . In this−1/2.The system displacement sensitivity  and the The double-anchored plate resonator B1 gave Therefore, the results achieved for In the case of the monolithic solution and capacitive readout ,11, as folutions ,10, that SMDD1/2 ,13 by 10solution ,17, withsolution  and Zhansolution  that proTherefore, the solution proposed in this work provides ultra-high displacement and capacitance resolution by means of a CMOS-MEMS monolithic approach in the sub-micrometer range both in air and vacuum conditions thanks to the overall system integration that minimizes the non-desired parasitic contributions. Depending on the application, the vacuum improvement is close to being e sensed . This alyF barrier being measurable both in air and vacuum conditions. Such a capacitance variation corresponds to an equivalent resonator displacement being in the fm range. This is possible thanks to the monolithically integrated CMOS-MEMS solution that reduces significantly the interconnect parasitics between the mechanical sensing part and the amplifier electronics—making use of a mature low-cost commercial 0.35-μm CMOS technology—and thanks to the ultra-low-noise amplifier design. Furthermore, these outcomes are orders of magnitude better than other monolithic CMOS-MEMS solutions and close to the opto-mechanical state-of-the-art devices as shown in fm. We have also obtained outstanding displacement sensitivities reaching values in the order of hundreds The results reported here demonstrate that the ultra-low-noise capacitive readout system integrated monolithically with the mechanical resonator achieves to resolve the thermomechanical fluctuations of four different resonators. The minimum capacitance change detected is close to the We have given proof that the un-driven measured output spectrum corresponds to thermomechanical noise coming from the Brownian motion of the resonators; the theoretical model developed matches the captured experimental data for all geometries accurately enough, emphasizing the frequency shift when changing the bias voltage due to the spring softening effect. Moreover, the theoretical model predicted the range of motional resistances allowed to be able to sense the resonator thermomechanical motion, which emphasizes the thermomechanical nature of the measured noise.In summary, this work demonstrates feasible ultrasensitive resonators, enabling the development of compact and light system on-chip sensing devices exploiting the ultimate limits of the sensor resolution for different applications that must operate in atmospheric conditions. Additionally, vacuum operation even improves in the


Evidences in literature strongly advocate the potential of immunomodulatory peptides for use as vaccine adjuvants. All the mechanisms of vaccine adjuvants ensuing immunostimulatory effects directly or indirectly stimulate antigen presenting cells (APCs). While numerous methods have been developed in the past for predicting B cell and T-cell epitopes; no method is available for predicting the peptides that can modulate the APCs.We named the peptides that can activate APCs as A-cell epitopes and developed methods for their prediction in this study. A dataset of experimentally validated A-cell epitopes was collected and compiled from various resources. To predict A-cell epitopes, we developed support vector machine-based machine learning models using different sequence-based features.A hybrid model developed on a combination of sequence-based features (dipeptide composition and motif occurrence), achieved the highest accuracy of 95.71% with Matthews correlation coefficient (MCC) value of 0.91 on the training dataset. We also evaluated the hybrid models on an independent dataset and achieved a comparable accuracy of 95.00% with MCC 0.90.http://webs.iiitd.edu.in/raghava/vaxinpad/ will facilitate researchers in designing peptide-based vaccine adjuvants.The models developed in this study were implemented in a web-based platform VaxinPAD to predict and design immunomodulatory peptides or A-cell epitopes. This web server available at The online version of this article (10.1186/s12967-018-1560-1) contains supplementary material, which is available to authorized users. Peptide subunit vaccines are hailed as an advancement over live or inactivated whole organism vaccines due to their ability to minimize adverse reactions . Yet, anVaccine adjuvants effectuate their action by a variety of mechanisms with all of them involving the antigen presenting cells (APCs) particularly the dendritic cells . One of Cationic host defense peptides (HDPs) were originally discovered as antimicrobial peptides produced within the multicellular organisms having a broad-spectrum activity against bacteria, viruses, fungi, protozoa, etc. . Of late+ versus CD4+ T cells, specific antibody types, etc. [Adjuvants have been incorporated into the vaccine formulations for qualitative alteration of the adaptive immune responses that are different from non-adjuvanted antigens. For instance, the adjuvants have been used to skew the immune responses with respect to Th1 (T-helper 1) cells versus Th2 cells, CD8Developing adjuvants based merely on empirical studies without the understanding of mechanisms is inadequate . There iIn such a scenario, in silico models to screen and identify potential vaccine adjuvant candidates could prove to be useful as the existing experimental approaches are time and resources consuming . PreviouIn the last two decades, numerous method have been developed for predicting potential of peptides to stimulate adaptive arm of the immune system that include methods for predicting MHC binders, B-cell epitopes –23 and TIn the present work, first we collected experimentally identified immunomodulatory peptides from the literature and included them in our positive set named A-cell epitopes. Next, we collected the human endogenously circulating peptides to build the negative set named A-cell non-epitopes. Combining the positive and the negative sets into a complete dataset, we developed support vector machine (SVM) based computational models that can classify a new query peptide as A-cell epitope or non-epitope. To benefit the users of the scientific community, we provided the best performing SVM-based prediction models in the form of a web-based application called VaxinPAD to be used for identifying and designing novel A-cell epitopes. Such peptides identified computationally might serve as the starting molecules for designing peptide-based vaccine adjuvants.Calliphora vicina, have been found to stimulate the cytotoxic anticancer activity of the human NK-cells and lymphocytes. In another case, a set of peptides as described in patent US8791061 B2 have been shown to enhance innate immunity by modulating the activity of type II transmembrane serine protease dipeptidyl peptidase (DPPIV) also known as CD26 or adenosine deaminase binding protein, expressed on major immune cells like activated T-cells, B-cells, NK-cells, macrophages and epithelial cells. With two major functions of signal transduction and proteolysis, the effects of DPPIV protein-mediated cellular processes include modulation of the chemokine activity by cleaving dipeptides from chemokine N-terminus that alters the receptor binding and specificity of the processed chemokine. DPPIV is a neutrophil chemorepellant and eosinophil chemoattractant too.The experimentally validated immunomodulatory peptide sequences were obtained from 16 patents. As an example of the sequences considered immunomodulatory, a set of sequences taken from a patent (US20110008318 A1), includes flagellin-derived peptides that exhibit immunomodulatory effect by direct binding to TLR 5 as indicated by assays reporting increased NF-κB expression estimated from coupled luciferase activity and TNFα production estimated using flow cytometry. In one of the patents (US7462360 B2), a class of immunomodulatory peptides, called alloferons, derived from the bacteria challenged blood of larvae of the insect blowfly, After removing the longer sequences, 304 unique sequences left in the length range of 3–30 residues were used to constitute the positive dataset named here as the A-cell epitopes. The upper bound of length 30 residues was kept as more than 90% of the originally collected epitope sequences were retained keeping this criterion used for removing very long sequences. In the absence of experimentally verified non-immunomodulatory peptides (non-epitopes), the experimentally identified endogenous human serum peptides , 33 wereIn order to develop any in silico model it is important to generate input features corresponding to each data point. In this study, a data point is the amino acid sequence of a peptide (either A-cell epitope or non-epitope). It is important to generate fixed length input features because machine-learning techniques require fixed length vector for developing a model. As the length of peptides is variable, thus we computed amino acid composition of A-cell epitopes and non-epitopes for developing models. We also computed the average amino acid composition of A-cell epitopes, non-epitopes and the human proteins, in order to understand compositional bias in A-cell epitopes. The amino acid composition for each sequence constituted the input vector of length 20, which was used for developing SVM-based prediction models. Similarly, the dipeptide composition vectors of length 400 were generated for A-cell epitopes and non-epitopes with each element of a vector corresponding to the composition value of each type of possible dipeptide. In addition to compositional features, we also generated binary features for developing models using fixed length of amino acids from the termini  of peptides. In the case of binary feature, an amino acid is represented by a vector of 20, where the presence of amino acid is indicated by ‘1’ and the absence is presented by ‘0’ . This meWe used the Motif—EmeRging and with Classes—Identification (MERCI) Program  to identIn the present study, some commonly used popular machine learning techniques were used to develop classification prediction models. We used WEKA package to implement these machine learning techniques namely Random Forest, Naïve Bayes, SMO and J48 . These clight [Subsequent prediction models in this study were developed using SVM, which has been frequently used to develop models for epitope prediction in previous studies , 23, 28.light  to selecIn this study, standard procedure was followed to evaluate the performance of models in order to avoid biases in performance due to over optimization. Our main dataset was divided into two categories internal and external dataset, where the internal dataset contained ~ 80% sequences and the external dataset comprised of the remaining 20% sequences. In order to perform internal validation, we performed fivefold cross validation technique on internal dataset. In this technique, the dataset is divided in five sets, four sets are used for training a model, and the remaining set is used for testing the model. This process is repeated five times so each sequence is tested only one time. In order to perform the external validation of a model, the best model developed using fivefold cross validation is tested on an external dataset. It is important to assess the performance of a model on external or independent dataset because the performance of a model in internal validation may be biased due to optimization of the model . The perIn order to avoid over fitting of models and reducing variance in performance of models; we used bootstrap aggregating (bagging) for averaging performance of models. In this study, process of creating internal and the external datasets has been repeated ten times. Each time, the sequences for the internal dataset were randomly selected from the main dataset, and the remaining sequences were included in external dataset. Finally, we evaluated the performance of our models using various features on both the internal as well as the external datasets as described in above sections. This process gave 10 performance values using internal and 10 performance values using external validation from 10 rounds of sampling. We computed the mean and standard deviations of these performance values to check for bias in performance of the models depending on the choice of sequences on which the models were trained or independently evaluated.As described above, initially the negative dataset consisted of the experimentally identified endogenous human serum peptides as non-epitopes constituting the negative dataset. We further wanted to check whether the performances of the classification models were dependent on the choice and size of the negative datasets. This was necessary as the negative dataset does not contain the experimentally verified non-epitopes. For this, we created an alternative negative dataset of random peptides derived from the human proteins obtained from the Swiss-Prot database. As mentioned in the previous section, for each of the 10 rounds of sampling, a different set of random peptides 10 times the number of the positive sequences (A-cell epitopes) from the human proteins was kept as the negative dataset.One of the objectives of this study is to understand the nature of A-cell epitopes regarding the residues preferred in A-cell epitopes. Thus, we computed the average residue composition of A-cell epitopes and the non-epitopes. The non-epitope dataset consists of peptides occurring in the normal human serum assumed to be non-immunomodulatory. In addition, the average residue composition of the Swiss-Prot Human proteins was also computed and compared with that of the A-cell epitopes.In the A-cell epitope dataset, the percentage composition of an amino acid residue was calculated for each epitope, and the average of these values was plotted in Fig. Similarly, the dipeptide and tripeptide compositions of the A-cell epitopes and non-epitopes were also compared with the Swiss-Prot Human proteins. Additional file http://www.twosamplelogo.org/cgi-bin/tsl/tsl.cgi) [We performed position-specific analysis of residues in A-cell epitopes to understand the type of residues preferred at different positions in A-cell epitopes. In this study, two-sample logo (TSL) tool (available at tsl.cgi)  was usedThe Motif—EmeRging and with Classes—Identification (MERCI) Program is a software that helps in finding the motifs exclusive to one class when compared to another class of sequences. Additional file n-mers  in the A-cell epitopes and non-epitopes. First, the occurrence of each type of n-mer was counted in all of the Swiss-Prot proteins, and the n-mers were arranged in increasing order of occurrence. In this order, the n-mers were divided into 8 bins such that the 1st bin contained the n-mers least abundant in Swiss-Prot while the 8th bin contained the most abundant n-mers occurring in the Swiss-Prot. Next, the percentage of n-mers in a particular bin that occur in the Swiss-Prot was calculated with respect to the total number of n-mers in Swiss-Prot. Similar percentage value was calculated for A-cell epitopes and non-epitopes for each bin, and the values were presented in the form of a plot in Fig. We compared the occurrence of peptide s n = 3, , 5, 6 inFigure light by from the dataset of 304 A-cell epitopes as positive sequences and 385 non-epitopes as negative sequences. From each of the positive and negative datasets, ~ 80% sequences were kept in the training–testing dataset while the remaining ~ 20% were kept in the independent dataset. Thus, the training–testing dataset had 243 positive and 308 negative sequences. The best performing models were selected on the basis of highest Matthews correlation coefficient values and a minimal difference between the sensitivity and specificity values.The sequence-based analyses like residue composition preferences; position-wise residue preference and motif search indicated that these features could help in discriminating the A-cell epitopes from non-epitopes. We developed SVM-based prediction models using SVMlight and four commonly used techniques  implemented using WEKA package. These models were developed using amino acid composition (AAC) and dipeptide composition (DPC) of peptide sequences (epitope and non-epitope). As shown in Additional file In order to understand, which machine learning technique will be most efficient for predicting A-cell epitopes, models were developed using different machine learning techniques. Initially models were developed using SVM implemented with SVMIn this study, we used bagging approach for sampling to overcome problem of over optimization or over fitting. Bagging procedure of sampling was adopted in this study to evaluate performance of models. The main dataset was divided ten times randomly into the internal and external datasets. Thus, we get ten training/internal datasets and ten independent datasets. The performance of all models was evaluated ten times on training and independent dataset. Finally, we computed the performance of each model in 10 rounds of sampling and reported the mean and standard deviation on these 10 datasets. Table The amino acid composition (AAC) and dipeptide (DPC) composition were used to develop SVM-based models on the training–testing dataset. On evaluating the performance parameters, the AAC model gave an accuracy of 93.30% and the Matthews correlation coefficient (MCC) value of 0.87 as given in Table Binary models take the residue position into account by representing each residue type as a binary vector. We considered 5 and 10 residue positions from either end of the peptide sequences (N and C termini) and developed SVM-based models individually and in combination. In case of 5-residue position consideration, the model developed on combined 5 residue positions on both the N and C termini  and consisted of ~ 20% of the total dataset resulting in 61 positive sequences and 77 negative sequences. The average performances of the AAC and DPC models on the independent dataset were comparable to those on the training–testing dataset with AAC model giving an accuracy of 93.91% and MCC of 0.88 while DPC model giving an accuracy of 94.64% and MCC of 0.89  10 times the number of A-cell epitopes. Bagging procedure of sampling was performed to create ten training and ten independent datasets for internal and external validation respectively. The DPC and DPC + motif models performed better than other models on the main dataset. As shown in Table http://webs.iiitd.edu.in/raghava/vaxinpad/). The platform has a couple of utilities that may help the user in designing peptide-based adjuvants as well enhance or diminish the immunomodulatory potential of the query sequence.For providing the SVM-based A-cell epitope prediction methods developed in the present study to the scientific community, we designed an in silico platform VaxinPAD . Arginine enrichment of the peptide sequences is an important aspect of increasing the cellular uptake of cell-penetrating peptides (CPPs) . Cathelin-mers found sparsely in the naturally occurring proteins. Patel et al. [Another aspect of our sequence analysis is the occurrence of l et al.  found thOn evaluating the performance of SVM models based on composition, the dipeptide composition showed no improvement over amino acid composition. The binary models also showed a lower performance than composition-based models. On the other hand, addition of the motif information increased the performance of both the amino acid composition model as well as dipeptide composition to achieve the maximum accuracies of ~ 96%. In our study, we implemented our best models- the dipeptide composition-based and that based on the hybrid of dipeptide composition and motifs. These models were better than other models possibly owing to the fact that the dipeptide composition provides more information in comparison to simple composition. Dipeptide composition provides the information about the amino acid fraction as well as their local order . It is wWe also checked whether the random distribution of the main dataset into the dataset used for training the models  and that evaluating them independently  renders a bias in the performance of prediction models. Further, the choice of sequences assumed to be the non-epitopes could also affect the performance of the prediction models. A low number of positive sequences in the total dataset could be a third source of influence on the robustness of prediction models. Using various methods, we observed that all of these three factors have a negligible effect on the performance of the best performing SVM-based prediction models for A-cell epitopes.The peptides designed using the tools developed in the present study might act by various mechanisms and receptors for activating the innate immunity owing to the fact that the training dataset of the prediction models contains peptides acting by diverse cell signaling routes. Hence, the in silico tool presented here could help an investigator to begin with a choice of peptides that may be the starting molecules for the development of vaccine adjuvants. However, there are certain limitations associated with this model, for example, the method does not consider modifications  and other topological aspects during model development. Secondly, whether the predicted peptides actually prove to be useful as adjuvants, would have to be tested experimentally. Another limiting aspect of the present study is the exclusion of very long immunomodulatory sequences and lastly, the size of the dataset used in the study. The model can be further optimized by incorporating more peptide features such as physico–chemical properties, modifications, etc. Also, with larger datasets and receptor-specific ligands made available in future, studies subsequent to the present investigation might help design peptides eliciting a specific desired innate immune response leading to adjuvancy. Nonetheless, VaxinPAD developed in this study for predicting the immunomodulatory peptides sets a stage for the advancement of rational peptide-based vaccine adjuvant designing.In silico methods for predicting and identifying DNA and RNA-based immunomodulatory molecules have already been developed , 14. Thehttp://webs.iiitd.edu.in/raghava/vaxinpad/ and http://crdd.osdd.net/raghava/vaxinpad/ freely to the scientific community.Host Defense Peptides have been realized as promising immunomodulators likely to become potential vaccine adjuvants . With imAdditional file 1: Table S1. Dataset (A-cell epitopes and non-epitope) used for training, testing and validation; including source of information. Table S2. The percent amino acid composition and difference in composition for A-cell epitopes, non-epitopes and human proteins including Students t-test with p-value and adjusted p-value. Table S3. The percent dipeptide composition and difference in composition in A-cell epitopes, non-epitopes and human proteins. Table S4. The percent tripeptide compositions of A-cell epitopes, non-epitopes and human proteins. Rows are sorted in decreasing order of values in the 5th column. Table S5. Motifs exclusively found in A-cell epitopes and their frequency of occurrence, sorted in the decreasing order of counts. Table S6. Motifs exclusively found in non-epitopes and their frequency of occurrence, sorted in decreasing order of counts. Table S7. Performance of various classifiers on the training–testing dataset and the independent dataset. Table S8. The performance of SVM-based A-cell epitope prediction models developed using various features; models were evaluating on training and independent datasets using fivefold cross-validation.


Cannabis sativa against malaria Plasmodium falciparum dihydrofolate reductase for antimalarial properties using Glide (Schrodinger maestro 2018-1). The result showed that phytochemicals from Cannabis sativa binds with a higher affinity andlower free energy than the standard ligand with isovitexin and vitexin having a glide score of -11.485 and -10.601 respectively, sophorosidehas a glide score of -9.711 which is lower than the cycloguanil  having a glide score of -6.908. This result gives newperception to the use of Cannabis sativa as antimicrobial agent.Available antimalarial drugs have been associated with numerous side effects, which include skin rashes and myelo-suppression.Therefore, it is of interest to explore compounds from natural source having drug-like properties without side effect. This study focuses onthe screening of compounds from  The prevalence of Malaria has been a major cause of mortality ininfants and adults globally Myriad of antimalarial drugs have been developed which includeschloroquine, quinolines, antifolates, hydroxyl-naphtha-quinonesand artemether Presently, dihydrofolate inhibitors have been developed for thecontrol of malaria. Still, the downside of their use is the ability ofPlasmodium falciparum dihydrofolate reductase to develop resistanceto these drugs. This occur as a result of mutation on the amino acidresidue at the active site of the enzyme leading to single, double,triple and quadruple mutation 5,6]. Mutation decreases thebinding affinity of the inhibitors, thereby decreasing the efficacy ofthe drug ,6. MutatGlide tool from Schrodinger molecular drug discovery suite(version 2018-1) was used in this research work.Eighty-one Characterized phyto-chemicals of Cannabis sativa usedin this study were obtained from published literatures and theywere used in the generation of library of compounds in this study.The library of compounds obtained was downloaded from NCBIPubChem database (https://www.ncbi.nlm.nih.gov/pccompound)in 2d (sdf) format. The phyto-chemicals generated were preparedusing the Ligprep interface in Schrodinger Crystallized three-dimensional structure of the target protein whichis Plasmodium falciparum dihydrofolate reductase-thymidinesynthase (pfDHFR-TS) in complex with co-crystallizedligand:cycloguanil, PDB ID:3UM8 The Receptor grid defines the area of interaction between theprotein and the ligand. This was carried out with the receptor gridgeneration tool in maestro 11.5 which defines the area around theactive site in term of co-ordinates x, y and z. The receptor grid boxresolution was centered at coordinates 29.72, 5.25 and 58.31corresponding to x, y and z-axis, respectively.The Docking analysis was accomplished using Glide tool onmaestro 11.5 The Hit compounds were further subjected to Absorption,Distribution, Metabolism, Excretion and Toxicity using the Qikproptool The docking protocol employed was validated by blasting the fastasequence of co-crystalized target protein with PDB ID: 3um8withthe CHEMBL database server (www.ebi.ac.uk/chembl/) Molecular interaction between protein and ligand predicts thebinding conformation or pose of the ligand bounded to the protein,which can be quantified, based on the shape and electrostaticinteraction between the ligand and protein The mechanism of interaction of potential inhibitors of plasmodiumdihydrofolate reductase has been exclusively studied both in wildtype and mutant type of the protein. Inhibition of the enzyme isdependent on the formation of different type bonds between theamino acid residue at the active site and the ligand. The eliminationof toxic effect that might result is due to the specificity of thecompounds to interact with the amino acid residues at the activesite of pfDHFR-TS. The amino acid residue of human DHFR differsfrom that of pfDHFR-TS by the replacement of residuePhe31,Gln35, and Asn64 in human with Met55, Cys /Arg59, and Phe116 inpfDHFR-TS The screening of compounds using Absorption, distribution,metabolism and elimination (ADME) describes the efficacy, abilityof the compounds to reach its target protein and to be easilyeliminated from the body. Computational approach to drug designhelp to screen large database of compounds in order to reduce thecost and time of subjecting diverse compound into molecularanalysis. The Lipinski's rule of five (ROF) enlist some criteria that isneeded for a compound to be considered to be drug like in nature,this criterion includes a molecular weight that is less than 500Da(<500Da), hydrogen bond donors that is less or equal to 5,hydrogen bond acceptors that is less or equal to 10 and octanolwaterpartition coefficient (logP) that is less than 5(<5). Therefore,compounds that are coherent with this rule are considered to bedrug-like in nature. From This study shows the binding ability of a library of compoundsgenerated from Cannabis sativa as potential inhibitors ofplasmodium dihydrofolate reductase. Isovitexin has a higherbinding affinity with pFDHFR-TS, interacting with amino acidresidue via hydrogen bonds and pi-pi stacking. This data providesa new perception and view into pharmacological use of Cannabissativa for malaria.


There are many diseases associated with latent viral infections. However, targeting latent viral infections remains a challenge for treatment. One of the difficulties is that there are few viral gene products that are expressed during latency to target with inhibitors. Therefore, it is important to understand the sequence variations in latent viral gene products. These sequence variations could affect the expression patterns of latent viral gene products and prevent certain sequence variants from being targeted by an antiviral molecule. In this issue, Marshall et al. dive deeper into answering these questions by analyzing genetic variation  and expression of latently-expressed viral microRNAs (miRNAs).Previously, this group had investigated the correlations of SNPs, expression, and disease in the context of Kaposi’s Sarcoma Herpesvirus (KSHV) infection and multicentric Castleman’s disease (MCD). In this latest report, they extend these studies in the context of another KSHV-associated disease, Kaposi’s sarcoma skin lesions from South African and American biopsies. Many of these newly discovered SNPs in the miRNA region were specific to the various KSHV subtypes. In a similar finding to their MCD study, they found the most variation in KSHV microRNA regions, miR-K12-8 and miR-K12-9. Umbach et al. [Following the detection of many new SNPs in the miRNA region of KSHV, this new report also investigated the potential impacts of these sequence variations on predicted structures and mature miRNA expression levels in the same clinical samples. Specific structural formations are necessary for normal RNA binding protein associations and miRNA biogenesis steps. The authors discovered that K12-8-3p and miR-K12-9-5p were expressed at lower levels in samples from South Africa, compared to American samples. In contrast, overall the expression levels of the majority of KSHV miRNAs were higher in the South African samples, despite having similar KSHV loads in the American samples. Additionally, they found SNPs in the mature miRNA regions of miR-K12-5, miR-K12-6, miR-K12-9, and miR-K12-10. Alterations of a single base with a mature miRNA can dramatically alter the mRNAs that are targeted by that specific miRNA. An interesting SNP (A121617G) near the start of pre-miRNA K12-3 was found in all of the South African samples and almost half of the American samples. This SNP correlated with expression changes in seven different mature miRNAs, suggesting more distant structural changes and changes in RNA-binding protein interactions that altered the mature miRNA expression pattern. These authors noted that some SNPs were discovered at sites near the 5’ end of the pre-miRNAs, which are important sites for association with the miRNA processing factors DGCR8 and Drosha. Structural predictions suggested that many of these SNPs would not disrupt the majority of miRNA hairpin structures.These new results present many interesting ideas. For example, how many of these SNPs directly correlate to changes in miRNA expression in experimental cell culture systems? The SNPs detected in MCD samples were previously tested in this fashion . With moFUNDINGThis research was supported by the Intramural Research Program of the NIH, NCI. The funder had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.