There is a documented need to build capacity for theory- and evidence-informed knowledge translation (KT) and patient engagement (PE) practice in health research. Dissemination of foundational content online coupled with social media promotion may build capacity by increasing awareness, knowledge, and positive attitudes.This retrospective study sought to (1) describe exposure and engagement of the KnowledgeNudge KT and PE dissemination strategy (online blog and Twitter profile) over 2 years and (2) identify and compare characteristics of individual posts with the most and least exposure and reach.t test. Individual post exposure was assessed by average post views per week. Individual post reach was assessed by average post reads per week. High- and low-profile blog posts with the highest and lowest 10th percentile for exposure and reach were identified.Exposure was assessed by blog site views per month and Twitter profile impressions per month. Engagement was assessed by Twitter profile interactions per month. Descriptive statistics were calculated for 6-month blocks and compared using one-way analysis of variance or Student P=.004) and reach (P<.001) during the final 6 months. Seven high-profile and 6 low-profile posts were identified. High-profile posts had a significantly greater average word count than low-profile posts (P=.003). There were no other significant differences between posts.A total of 99 posts and 755 tweets were published during the study period. There was a significant increase in exposure (The increases in KnowledgeNudge exposure and engagement offer preliminary evidence in support of this dissemination strategy for the practice of KT and PE. Variation in individual post exposure and reach warrants further exploration to tailor content to user needs. Future work will include a prospective evaluation strategy to explore the effect of KnowledgeNudge on awareness, knowledge, attitudes, and behavior. Knowledge translation (KT) is an evolving discipline dedicated to advancing the synthesis, exchange, dissemination, and application of knowledge to optimize health, health care delivery, and the health care system . It is aAccordingly, the need to build capacity to practice theory- and evidence-informed KT and PE has been identified in multiple studies -8. For eDissemination of foundational resource material may help to build capacity for practicing theory- and evidence-informed KT and PE by facilitating distribution and awareness of seminal works, current best evidence and practices, and ongoing critical debates in the field . In turnTo address the established need to build capacity for practicing evidence-informed KT and PE, the KnowledgeNudge dissemination strategy was developed and launched in 2016. KnowledgeNudge consists of an online blog (a web-based collection of self-published content)  and accoThere is consistent recognition of the need for outcome evaluation in established KT process models  and bestThe primary objective of this study was to describe and determine changes in exposure and engagement of the KnowledgeNudge blog and Twitter profile over a 2-year period (objective 1). The secondary objective was to identify and compare characteristics of individual posts with the most and least exposure and reach (objective 2). For the purpose of this study, exposure was measured through blog site views and Twitter profile impressions, and engagement was evaluated through Twitter profile interactions. Individual post exposure was evaluated through post views and reach through post reads.A retrospective descriptive quantitative study was conducted from August 1, 2016, through July 31, 2018. Given the nonidentifiable nature of the secondary data used for analysis, research ethics approval was not sought per Article 2.4 of the 2014 Government of Canada Tri-Council Policy Statement on Ethical Conduct for Research Involving Humans .For objective 1 (describe and determine changes in exposure and engagement of the KnowledgeNudge blog and Twitter profile), study data were extracted from standard use metrics available for the KnowledgeNudge blog site account (hosted on WordPress from August 2016 to February 2017 and on Medium from March 2017 to July 2018) and KnowledgeNudge Twitter profile. For objective 2 , metrics for individual posts were collected on October 1, 2018, allowing the last post in the study period  to accumulate metrics for 68 days. Individual post data were not available for the period August 2016 to February 2017 due to the change in site host and the inability to retrospectively retrieve individual post data from WordPress once the account was closed.The primary study outcomes were exposure and engagement of the blog site and Twitter profile (objective 1), as well as individual post exposure and reach (objective 2) ,24. ExpoDescriptive summary statistics were calculated for all variables . To determine characteristics of individual posts, a combination of deductive and inductive coding was used. First, the research team met and developed a coding framework that consisted of two broad coding categories by topic (KT and PE) and three subcategories by type . Practice posts were defined as those providing information on tools and resources for KT and PE; conceptual posts were defined as those providing evidence-based information on the science of KT and PE based on peer-reviewed literature; and opinion posts were defined as those providing expert opinion on KT and PE science and practice. Two team members independently coded individual posts. An additional category was included for posts that specifically identified as relevant to both KT and PE, and all other posts that did not fit in the developed categories were coded as other . Coding disagreements were resolved through discussion. Kappa scores were calculated to determine interrater reliability of individual post coding, which was found to be strong for post topic (𝜅=.85) and moderate for post type (𝜅=.66) .P<.05.To determine changes in exposure and engagement over time (objective 1), a 1-way analysis of variance was conducted to assess average blog site exposure over time and Twitter profile exposure and engagement for each 6-month block. Post hoc comparisons were completed using the Tukey honestly significant difference (HSD) test. Statistical significance was set at t test  views per month) than the first (823 [SD 275] views per month) and second (944 [SD 248] views per month) 6-month blocks (P=.001) and the third (1283 [SD 432] views per month) 6-month block (P=.003). There was no significant difference in average blog site exposure between the first, second, and third 6-month blocks.Monthly exposure and engagement are displayed in F3,20=9.0, P<.001). Post hoc comparison using the Tukey HSD test showed that average Twitter exposure significantly increased from the first 6-month block  to the third 6-month block  and to the last 6-month block . Post hoc comparison using the Tukey HSD test also revealed a significant increase in Twitter exposure between the second 6-month block , third 6-month block (P=.02), and last 6-month block (P=.02).Average Twitter exposure was 22,320 (SD 9139) impressions per month . A significant increase was seen in exposure over time . Post hoc comparison using the Tukey HSD test showed a significant increase in average Twitter engagement between the first 6-month block (220 [SD 119] engagements per month) and the third 6-month block . There were no other significant differences between the 6-month blocks.Average Twitter engagement was 294 (SD 124) engagements per month (range 57 to 554). There was a significant effect of time on average engagement  and reach . The word count of high-profile posts was significantly greater than that of low-profile posts . There was no significant difference in the number of tweets per post between high- and low-profile posts . There was no significant difference between high- and low-profile posts in terms of time of publication (P=.66), topic (P=.12), or type (P=.44). Characteristics of individual high- and low-profile posts are reported in The average exposure of individual posts was 4.8 (SD 8.8) views per week (range 0.3 to 79). The average reach of individual posts was 1.7 (SD 1.7) reads per week (range 0.1 to 12). The average word count of individual posts was 988.3 . The average number of tweets per post was 7.1 . Seven posts were identified as high profile, and 6 posts were identified as low profile. Comparison between high- and low-profile posts using a Student The goal of this study was to explore changes in exposure and engagement of the KnowledgeNudge KT and PE dissemination strategy during its initial 2-year period. By formally measuring and documenting changes in exposure and engagement of the KnowledgeNudge strategy, this study adds to the growing body of literature on the use of social media in dissemination science and demonstrates important contributions for building capacity in the practice of high-quality KT and PE practices. The findings establish a foundation for future studies to explore in-depth the impact of KnowledgeNudge content on KT and PE practice behaviors.An important finding was the significant increase in blog site exposure between the first and last 6-month periods, providing evidence of increased spread of information on foundational issues of KT and PE. The significant increase in Twitter profile exposure during the study also provides evidence of growing network size. The absence of significant changes in Twitter profile engagement between the first and last 6-month periods is arguably less important, as the Twitter profile served to encourage users to visit the primary blog site and was not the primary source of KT and PE content. We also observed considerable variation in reach among the individual posts. Post topic and type coding did not suggest any trends influencing variation between posts with the highest and lowest reach.The findings of this study are consistent with published evaluations of exposure and engagement in online dissemination blog strategies and Twitter activity in related domains of health -30. The Although we did not directly assess factors that contributed to the increase in blog site exposure, using Twitter as a promotional strategy has been associated with increase in website traffic ,32. For The findings related to characteristics of high- and low-profile posts have important implications for those planning online dissemination strategies in general and those specifically interested in building capacity for KT and PE practices. Among the blog characteristics tested, the only significantly different variable between high- and low-profile posts was word count. Notably, high-profile posts had significantly more words than low-profile posts. This finding is supported by some evidence suggesting longer blogs are more influential in terms of garnering reader attention and feedback . We founWe acknowledge the limitations of this retrospective study and potential for continued evaluation to overcome them. First, we recognize that reliance on online use metrics provides only a proxy indicator of awareness and generally relies on the assumption that the reader is actively interacting with the content. Analysis of related indicators such as Medium comments or claps (Medium’s version of likes) may have provided additional evidence for active engagement and awareness with the KnowledgeNudge strategy, although the inherent difficulty of accessing, measuring, and interpreting social media metrics is recognized in the literature . RetrospFuture research opportunities for understanding the effects of the KnowledgeNudge dissemination strategy include (but are not limited to) additional analysis to explore factors influencing variation in individual post engagement , social network analysis based on KnowledgeNudge Twitter and/or Medium followers, and a prospective study examining the overall impact of KnowledgeNudge on knowledge, skills, and attitudes toward theory- and evidence-informed KT and PE practice. Recognizing the limitations of dissemination strategies on behavior  and giveThe KnowledgeNudge dissemination strategy demonstrated increased online blog site and Twitter exposure over an initial 2-year period. Growth of KnowledgeNudge resulted mostly from an increase in blog site and Twitter exposures. The outcomes included in this study, based on standard use data, provide evidence of a foundational component for increasing capacity for theory- and evidence-informed KT and PE practice: access to information. Critical next steps include ongoing evaluation to explore the effects of KnowledgeNudge on knowledge, skills, and behavior. Variation in individual post reach warrants further exploration and audience feedback to tailor content to user needs. Future work will include a prospective evaluation strategy to comprehensively explore the effect of KnowledgeNudge on knowledge, attitudes, and behavior, and opportunities to leverage KnowledgeNudge resources in an active training program will be explored.


Genetics in Medicine;published online 25 October 2018; 10.1038/s41436-018-0339-3Correction to: The article has been corrected to account for one patient being investigatedthrough genome sequencing rather than exome sequencing as originally published; thusamendments to the Abstract and Methods have been made as well as addition of therelevant authors and acknowledgment.


The mechanism and rupture process of the giant 2011 Tohoku-oki earthquake (Mw 9.0) are still poorly understood due to lack of permanent near-field observations. Using seismic arrival times recorded by dense seismograph networks on land and at ocean floor, we determine a detailed seismic tomography model of the megathrust zone beneath the Tohoku forearc. Our results show that the coseismic slip of the 2011 Tohoku-oki earthquake initiated at a boundary between a down-dip high-velocity anomaly and an up-dip low-velocity anomaly. The slow anomaly at shallow depths near the Japan trench may reflect low-rigidity materials that are close to the free surface, resulting in large slip and weak high-frequency radiation. Our new tomographic model can account for not only large slip near the trench but also weak high-frequency radiation from the shallow rupture areas. Using data recorded by a new seafloor seismic network, the authors reveal the detailed 3D structure of the source zone of the great 2011 Tohoku-oki earthquake, which sheds new light on the mechanism of the great earthquake and tsunami. The mechanism of the large slip near the trench has been interpreted by different models, such as abundance of weak clay (smectite)12 and fault weakening13. A depth-variation frictional model was used to account for its energy radiation distribution16. However, the mechanism and rupture process of the great 2011 Tohoku-oki earthquake are still a matter of some controversy due to the lack of permanent near-field observations17.The great 2011 Tohoku-oki earthquake (Mw 9.0), one of the greatest earthquakes recorded by modern instruments, occurred in a megathrust zone formed by the subducting Pacific plate and the overriding Okhotsk plate  suggest that the huge shallow slip may be caused by weak clay (smectite) on the upper boundary of the subducting Pacific plate20. However, using residual topography and gravity anomalies, Bassett et al. 21 suggested that the structure and frictional properties of the overriding Okhotsk plate control the interplate coupling and seismogenic behavior in NE Japan. Nishikawa et al. 22 suggest that different slip behaviors exist in the Tohoku forearc, which may be caused by along-strike variations in pore fluids and lithology of the overriding and subducting plates. Previous tomographic studies25 of the Tohoku megathrust zone suggested that the 2011 Tohoku-oki earthquake hypocenter was located in a significant high-velocity (high-V) anomaly, which may represent an asperity in the megathrust zone. These studies have improved our understanding of the structural variation along the plate boundary. However, all the previous tomographic models have limited spatial resolution in the large-slip area near the Japan trench due to the lack of near-field seafloor observation.The mechanism of great megathrust earthquakes is influenced by the frictional properties, structure and composition of the plate boundary fault26. The deployment of the S-net provides us with an unprecedented opportunity to image the structure of the Tohoku megathrust zone and to clarify the mechanism of megathrust earthquakes. Using a large number of high-quality arrival-time measurements of local earthquakes recorded by the S-net27 and Hi-net28, here we investigate the detailed three-dimensional (3-D) seismic velocity structure beneath the Tohoku forearc, which sheds new light on the mechanism and rupture process of the great 2011 Tohoku-oki earthquake.Recently, the Seafloor Observation Network for Earthquakes and Tsunamis (S-net) Fig.  has been25, and the obtained results  earthquakes and historical great earthquakes occurred, which was designated as the Sanriku-oki low-seismicity region29. At shallow depths <20 km, our Vp model  may play a key role in the dynamic weakening processes. Recent numerical simulations32 suggest that the low shear strength of weak clay minerals is insufficient to arrest the inertial motion of rupture propagating along the megathrust, and so large slip could occur near the trench axis.One of the most striking characteristics of the great 2011 Tohoku-oki earthquake is its large coseismic slip at the shallow depth near the Japan trenchM ≥ 7.0) that occurred before 2011 are mostly located in the deeper high-V and high-Q  zones with strong ground motions and positive residual gravity35 , the up-dip low-V anomaly may have been able to arrest rupture propagation to the shallow part due to their relatively low slip velocities. However, for the great 2011 Tohoku-oki earthquake, the low-V anomaly at the shallow depth may not have arrested up-dip rupture due to the large strain rate changes resulting from the extraordinary large slip near the hypocenter. The low-V anomaly with low rigidity may cause not only large coseismic slips near the trench but also a deformed upheaval structure at the shallow depth5. The low-V anomaly near the Japan trench may be also responsible for a preceding slow slip event (M 7.0) in the source zone36  show distinct land-ward displacement rates in the large coseismic slip area and remarkable trench-ward displacement rates in the south of the FSB  that are located in a high-V anomaly and show small trench-ward movements , we can obtain more accurate ray paths and get a better tomographic modelExtensive checkerboard resolution tests (CRTs) are performed to evaluate the adequacy of ray coverage and the spatial resolution of our tomographic model (Supplementary Figs. Supplementary InformationPeer Review File


Whole genome sequences of SARS-CoV-2 obtained from two patients, a Chinese tourist visiting Rome and an Italian, were compared with sequences from Europe and elsewhere. In a phylogenetic tree, the Italian patient’s sequence clustered with sequences from Germany while the tourist’s sequence clustered with other European sequences. Some additional European sequences in the tree segregated outside the two clusters containing the patients’ sequences. This suggests multiple SARS-CoV-2 introductions in Europe or virus evolution during circulation. An outbreak of a viral respiratory illness  caused by the newly discovered severe acute respiratory syndrome coronavirus SARS-CoV-2), started around mid-December 2019, in the city of Wuhan, Hubei province, China , started, where tTo gain further understanding on the molecular epidemiology of the outbreak in Italy, we characterised the full-genome sequence of two SARS-CoV-2 strains respectively isolated from two patients diagnosed in the country. The first patient was a Chinese tourist from Wuhan diagnosed at the end of January, who had visited Rome and not been in areas of Italy later found to be the initially affected areas of the epidemic in Lombardy. The second patient was an Italian person, with no apparent direct epidemiological link with China and who was diagnosed in the second half of February in Lombardy. The sequences presented are analysed in the context of other available genome sequences from Europe and elsewhere.The two patients in this study had both been hospitalised with an acute respiratory illness (pneumonia), showing a bilateral lung involvement with ground-glass opacity, requiring intensive care. The Chinese patient had had onset of symptoms on 29 January 2020 and had been diagnosed in a hospital in Rome. The Italian patient whose onset of symptoms had occurred on 10 February 2020 had been diagnosed in a hospital in Milan. Biological samples from both patients had been confirmed as being SARS-CoV-2 positive by the National Reference Laboratory (NRL) of the Istituto Superiore di Sanità (ISS) in Rome.www.geneious.com) [https://www.gisaid.org/epiflu-applications/next-hcov-19-app/).The samples used for this study were nasopharyngeal swabs. These had been respectively sampled on the same day of hospitalisation, when symptoms occurred, for the Chinese tourist and 10 days after symptom onset for the Italian patient. An aliquot of each patient’s nasopharyngeal sample was used to generate in vitro cultures in Vero cells grown in modified Eagle’s medium  supplemented with GlutaMAX. A total of 140 µL of each culture’s supernatant was used for viral RNA extraction using the QIAMP VIRAL RNA mini kit . The obtained genomic RNAs were retro-transcribed using the SuperScript III Reverse Transcriptase kit ) and double-stranded DNAs were subsequently obtained by Klenow enzyme  according to the manufacturer’s instructions. The Nextera XT kit was used for library preparations and whole genome sequencing was performed using the Illumina Miseq Reagent Nano Kit, V2 2 x 150 cycles) on the Illumina MiSeq instrument . The reads were trimmed for quality and length and assembled by mapping to the reference genome from Wuhan, China (GenBank accession number: NC_045512.2) using Geneious Prime . Sequence alignment was performed using MUltiple Sequence Comparison by Log- Expectation (MUSCLE) software  [https://www.megasoftware.net/) [To analyse the obtained SARS-CoV-2 genomes respectively derived from the infected Chinese tourist (GISAID accession ID: EPI_ISL_412974) and the Italian patient (GISAID accession ID: EPI_ISL_412973) in a phylogenetic context, a dataset of 40 available SARS-Cov-2 complete genomes from different countries was retrieved from GISAID  . EstimatThe maximum likelihood phylogenetic tree in the The genome sequence from the Italian patient in Lombardy (EPI_ISL_412973) appeared in contrast to be located in a different cluster including two genome sequences from Germany (EPI_ISL_406862 Bavaria/Munich and EPI_ISL_412912 Baden-Wuerttemberg-1) and one genome sequence from Mexico (EPI_ISL_ 412972),  composition and the potentially resulting variable amino-acids in derived protein sequences compared with the Wuhan reference sequences (MN908947 and NC_045512), were investigated for the genome sequences retrieved in this study, as well as three other genome sequences  that clustered with the sequence of the patient in Lombardy.The genome-wide SNPs are reported in The genome sequence from the Chinese tourist hospitalised in Rome differed in two nt positions from that of the COVID-19 patient in Wuhan (NC_045512), while the genome sequence isolated from the Italian patient showed four nt variations . For the sequence of the Chinese tourist, the first SNP inside ORF1ab  did not result in an amino acid change.In the The sequence of the Chinese tourist hospitalised in Rome on 29 January (EPI_ISL_412974) presented a mutation 3606F in ORF1ab with respect to the reference Wuhan genome (L). In ORF3a, this sequence had a V at amino acid position 251, as opposed to a G in the references from Wuhan.Meanwhile, the sequence of the Italian patient from Lombardy (EPI_ISL 412973) presented an L at amino acidic position 4704 with respect to the reference Wuhan genome (P). It also had a mutation in the surface glycoprotein, at amino acidic position 614, where it showed a G compared to the reference sequences from Wuhan that presented a D at that position.With regard to the nucleocapsid protein, both of the sequences from the Italian patient and Chinese tourist presented the same amino acids of the references Wuhan genomes.In this study, the full length genomes of two SARS-CoV-2 strains (EPI_ISL_412973 and EPI_ISL_412974) isolated in Italy, one from an Italian patient, the other from a Chinese tourist visiting Rome, are completely sequenced and analysed, after virus cultivation. Compared to the viral genome sequence of the COVID-19 patient in Wuhan, the sequence from the Chinese tourist had two nt differences, while that of the Italian patient had four. Phylogenetic analysis consistently placed the Italian patient’s strain in a distinct cluster from the tourist’s strain. The strain of the Italian patient grouped with other viral strains identified in Germany and Mexico, while the strain from the Chinese tourist, related with the Wuhan virus strain, clustered with different European strains and a strain from Australia. Other sequences from strains collected in Europe, which were included in the phylogenetic analysis, ended up in separate clusters from the ones respectively containing the sequences of the two patients reported here. The results are consistent with several introductions of SARS-CoV-2 in Europe and/or further circulation of the single strain originating in Wuhan with concurrent evolution and accumulation of mutations. The mutations found in the virus identified in Lombardy, compared with the reference Wuhan strain, and the identification of amino acids changes, should be further investigated to understand whether they may affect virus characteristics. Some limitations need be mentioned: first, the lack of epidemiological information available with most sequences deposited in the database; second, the number of genomes available at the time of the analysis and consequently their selection. Nevertheless, these data may be useful to understand the dynamics of the local transmission of SARS-CoV-2 in Europe.


The Conference was focused on the discussion of the research on medical genetics and sequencing, and new omics technologies.Current medical genetics research is oriented on next-generation sequencing technologies, genomics studies , 2. Thishttp://conf.bionet.nsc.ru/sbb2019/en/). We have published selected conference materials as special issues at BMC Genetics and related BioMed Central journals [This journal issue contains materials on genetics and medical genetics presented in 2019 at the conference in Moscow and SBB-2019 (Systems Biology and Bioinformatics - 2019) School in Novosibirsk. The SBB School series on bioinformatics is organized annually since 2008 by the Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences and Novosibirsk State University  has been investigated as a potential susceptibility gene for schizophrenia.We open up this Special Issue by the population genomics study on schizophrenia by Evgeniya Poltavskaya et al.  (this isPIP5K2A rs8341 and rs946961 showed significant association with course of schizophrenia (continuous or episodic). The experimental data confirm that PIP5K2A is a genetic factor influencing the type of course of schizophrenia in Siberian population. Disturbances in the phosphatidylinositol pathways may be a possible reason for the transition to a more severe continuous course of schizophrenia. The studies on medical genetics problems on Siberian populations were presented in [The authors studied the possible association between eleven polymorphic variants of PIP5K2A and the clinical features of schizophrenia in a population of 384 white Siberian patients with schizophrenia using genotyping. ented in , 14.The work by Xianping Meng and colleagues  (this isSP1 in post-stroke patients. Deep vein thrombosis (DVT) has been well-known to be associated with stroke, which is also supported by many clinical studies [SP1 could be a novel therapeutic target gene for post-stroke treatment.Xixi Xiang and co-authors  . We invite our readers worldwide to attend the systems biology meetings in Russia - Digital Medicine Forum  and MGNGS-2020  event postponed to 2021 (http://ngs.med-gen.ru/mgngs20/).Overall, this journal issue includes reports of recent medical genetics applications, as well as case reports, continuing series on BMC Med Genetics and BMC Med Genomics special post-conference journal issues , 2. We h


Glioblastoma (GBM) is the most malignant primary brain tumor, for which improving patient outcome is limited by a substantial amount of tumor heterogeneity. Magnetic resonance imaging (MRI) in combination with machine learning offers the possibility to collect qualitative and quantitative imaging features which can be used to predict patient prognosis and relevant tumor markers which can aid in selecting the right treatment. This study showed that combining these MRI features with clinical features has the highest prognostic value for GBM patients; this model performed similarly in an independent GBM cohort, showing its reproducibility. The prediction of tumor markers showed promising results in the training set but not could be validated in the independent dataset. This study shows the potential of using MRI to predict prognosis and tumor markers, but further optimization and prospective studies are warranted.IDH)-wild type GBM. Predictive models for IDH-mutation, 06-methylguanine-DNA-methyltransferase (MGMT)-methylation and epidermal growth factor receptor (EGFR) amplification using imaging features were developed using machine learning. The performance of the prognostic model improved upon addition of clinical, VASARI and radiomics features, for which the combined model performed best. This could be reproduced after external validation (C-index 0.711 95% CI 0.64–0.78) and used to stratify Kaplan–Meijer curves in two survival groups . The predictive models performed significantly in the external validation for EGFR amplification (area-under-the-curve (AUC) 0.707, 95% CI 0.582–8.25) and MGMT-methylation  but not for IDH-mutation . The integrated clinical and imaging prognostic model was shown to be robust and of potential clinical relevance. The prediction of molecular markers showed promising results in the training set but could not be validated after external validation in a clinically relevant manner. Overall, these results show the potential of combining clinical features with imaging features for prognostic and predictive models in GBM, but further optimization and larger prospective studies are warranted.Glioblastoma (GBM) is the most malignant primary brain tumor for which no curative treatment options exist. Non-invasive qualitative ) and quantitative (radiomics) imaging features to predict prognosis and clinically relevant markers for GBM patients are needed to guide clinicians. A retrospective analysis of GBM patients in two neuro-oncology centers was conducted. The multimodal Cox-regression model to predict overall survival (OS) was developed using clinical features with VASARI and radiomics features in isocitrate dehydrogenase ( Glioblastoma (GBM) is the most malignant type of primary brain cancer with an incidence of 2–3 cases per 100,000 [MGMT) methylation status, which is predictive of an improved response to alkylating chemotherapy such as TMZ [MGMT methylated and unmethylated patients still exists for which the efficacy of TMZ is still to be determined [IDH) genes—which has been identified as a positive prognostic marker—is linked to dedifferentiated low-grade gliomas which have a distinctly different clinical behavior compared to IDH wild-type (WT) GBM [EGFR) amplification is one of the most common genetic alterations (±50%) in GBM [EGFR amplification as a prognostic factor still remains controversial [EGFR have so far been unsuccessful but are still ongoing [GBM is diagnosed using gadolinium contrast-enhanced magnetic resonance imaging (MRI) followed by histopathological examination of tumor tissue specimen obtained after either biopsy or resection. Further characterization of GBM has led to the introduction of the 2016 updated world health organization (WHO) classification of central nervous system tumors . This cltermined . Additio(WT) GBM . Epiderm) in GBM . This on) in GBM ,11. Howeoversial ,13 and s ongoing . Intratumor heterogeneity complicates treatment efficacy as different regions within the same tumor may contain cells having distinct genetic compositions, transcriptional subtypes and/or proliferation kinetics . FurtherIDH-mutation status is established as the best prognostic marker in GBM [IDH wild-type GBM prognostic subgroups is still warranted due to their heterogeneous prognosis and clinical behavior.Imaging techniques have the advantage over standard pathological examination to also analyze the invasive, non-resected, components of GBM and thus capture and analyze the tumor as a whole. Especially temporal heterogeneity of expression of molecular targets cannot be evaluated using routine clinical diagnostics, as re-resection of tumors is not always feasible, making non-invasive imaging an interesting alternative. In order to make a standardized analysis of qualitative MR imaging features, the Visually Accessible Rembrandt Images (VASARI) features were previously developed . VASARI r in GBM , defininThe main challenge in developing prognostic and predictive imaging-based models is their generalizability towards all GBM patients treated at different centers. Differences in diagnostic techniques  and treatment and population variety can greatly influence model performances . Due to IDH1/2 wild-type (IDH-WT) GBM. Furthermore, the value of imaging features as predictor for clinically relevant molecular markers for GBM was explored. The objective of this study was to investigate the additive value of qualitative and quantitative imaging heterogeneity analysis to established prognostic clinical features. These data were used to develop a prognostic model for OS in a real-world multi-center GBM population for p-value, 0.001). Patients in the validation cohort more frequently received no adjuvant treatment, but these data were not available for all patients. Patient demographics, received treatment schedules and tumor characteristics are listed in In total, 142 patients were included in the training cohort and 46 patients in the validation cohort. Median OS was 12.0 months  in the training cohort and 7.3 months  in the validation cohort  in the training cohort and 7.0 months 0.4–29.4 months) in the validation cohort in the analysis . The mulanalysis . In thisanalysis . Additioanalysis . An elab.4 monthsp-value 0.27), indicating there is no certainty for the slope in the validation set being different from 1. The joint test of all predictors with the offsetting of the predicted PI results in the p-value of 0.23, indicating that there is no evidence of a lack of fit on the validation.Clinical features that were selected in the clinical model were chosen based on previous studies  and clinn = 38) and the discriminative prognostic value in both cohorts was analyzed using Harrell’s C-index (n = 129). In order to make a comparison between the different models, the C-index for the VASARI-only model was also calculated using only the patients available in all other models (n = 95). In order to visualize the prognostic potential of the integrated imaging and clinical model (Model 7), the data-set was split in a low- and high-risk group at a set cut-off value (75th percentile) of the prognostic index in the training cohort. This same cut-off value was applied to the external validation cohort. Two survival groups could be identified  in both the training and validation cohort , the Maastricht University Medical Center+ (MUMC+) cohort was split into a training (70%) and test (30%) cohort. For the prediction of EGFR amplification, in total eleven VASARI features and four radiomics features were selected in the predictive models using the XGBoost machine learning algorithm  and three radiomics features   in the test dataset but did not perform as well in the external validation dataset (AUC 0.667 (95% CI 0.522–0.820); The predictive models developed for gorithm) . VASARI IDH1 mutation ten VASARI features were included in the multivariate VASARI model and nine radiomics features in the radiomics prediction model developed using the XGBoost machine learning algorithm  score calculated for this study was 47%. An overview of point allocation towards the TRIPOD statement and RQS score can be found in Increasing curation rates by optimizing treatment strategies is being hampered by the highly invasive nature and GBM specific inter- and intratumoral molecular heterogeneity. MR imaging is currently the preferred diagnostic imaging technique for GBM. However, integrated standardized qualitative and quantitative analysis of different MR sequences has not yet been introduced into prognostic and predictive GBM models. This study retrospectively analyzed two multi-center GBM patient cohorts to develop integrated clinical and imaging prognostic models and predictive models for clinically relevant molecular markers. EGFR amplification and IDH1-mutation in the test cohort, none of the predictive models for molecular markers were able to predict these markers in a clinically relevant manner in the external validation set.Combining clinical features with quantitative and qualitative imaging features resulted in the most optimal prognostic model which could be reproduced in the external validation cohort . Despite promising results for predicting IDH-WT GBM patients as this patient group makes up the majority of GBM and exhibits large variation in prognosis and treatment response. This variance is also reflected in statistically significant differences in baseline characteristics for OS and MGMT-methylation. However, these differences are also known to exist between centers, in which different treatment decisions and strategies are being implemented. The aim of this study was to investigate the performance of prognostic models in such heterogeneous GBM cohorts. To predict OS, five VASARI features were identified to be of most prognostic relevance. Three of these features are well known prognostic factors and were also previously identified to be negatively associated with OS  and can be attributed to a more invasive growth of the tumor [The prognostic model described in this study is developed for he tumor ,33. The he tumor ,35,36,37he tumor ,38.Radiomics features that were identified to have prognostic value were mainly derived from T2-weighted imaging. This is in line with the hypothesis that the T2-weighted signal corresponds with intratumor heterogeneity and infiltrative tumor growth  and thisp-value < 0.001)  and became clinically relevant. The robustness of this combined model also improved as the model performed similarly in the training- and validation cohort and the uncertainty decreased as represented by a smaller confidence interval of the C-index. Model 5 and 6 report similar performances when compared to the model combining all features. However, the final combined model seems to remain mostly stable between both cohorts, though the actual additive value should be further validated in larger patient cohorts. The combined model was also able to accurately split the two cohorts in a high- and low-risk group (< 0.001) B,C. PrevIDH1-mutation, MGMT-methylation and EGFR amplification, by machine learning approaches. Overall, the predictive models had promising performance on the test set, especially when VASARI and radiomics features were combined  for T2_original_firstorder_10Percentile, T1_wavelet_HLL_glcm_DifferenceAverage features, which indicates the ability of these features to reflect the heterogeneity in the outcome  is an established prognostic feature which could not be included in this study due to lack of reporting of the KPS in patient files during the time period used for this study. Furthermore, it could be stated that a limitation of this study was the lack of advanced MRI sequences such as diffusion- and perfusion-weighted imaging and PET-MRI. However, this study specifically chose to focus on the relevance of conventional MRI images as these are widely available in clinical centers. Furthermore, MRI radiomics features are known to be dependent on differences in MRI scanners and scanning protocols. The images used in this study were collected from more than ten different hospitals over a ten-year time-period resulting in large differences in technical MRI characteristics. Again, even though this limits the performance of radiomics, an ideal prognostic and predictive model should not be dependent on homogeneous data. These differences in MRI acquisition methods are present in the real-life multicenter setting and should be accounted for in order to provide a relevant, clinical applicable model.Several limitations should be taken into account when considering the results of this study. The main limitation of this study is the number of patients that were included. Though for the OS models the number of patients is in accordance with the majority of previous studies, especially the limited available molecular data in the external validation set limits the validation capacity of the predictive models. Especially In order to further improve the prognostic and predictive potential of non-invasive imaging models, several steps need to be taken. First of all, larger (big data) datasets and preferably prospective studies are warranted to develop more accurate and generalizable models. This could pose a challenge, especially in less common types of cancer such as GBM. Next, the first studies on radiomics have been conducted on computed tomography (CT) imaging, which can be quantified using standardized Hounsfield units. For MRI radiomics, such a unit does not exist which poses problems due to inter- and intra-scanner variability. Multiple pre-processing methods have been developed, though not all radiomics features were shown to be robust between different pre-processing approaches ,58,59. TParallel to the establishment of MR signatures that are able to predict clinically significant expression of specific biomarkers, there is a need for imaging signatures that capture the level of intratumoral heterogeneity. However, it needs to be emphasized that is not yet clarified how to quantify GBM MR imaging heterogeneity and moreover how to non-invasively analyze the level of intratumoral heterogeneous expression of predictive markers, since the golden standard, single cell RNA sequencing, is missing in standard of care. By extracting radiomics features from the whole tumor and the surrounding area of edema we identified several features that are associated with intratumor heterogeneity. However, different steps could be taken to include more aspects of tumor heterogeneity. Improved performance of radiomics has been reported when features are extracted from distinct tumor areas  separately ,66, thouAll patients treated by the neuro-oncology team of the Maastricht University Medical Centre  between January 2004 and August 2014 for a glioblastoma (WHO grade IV) were considered for inclusion in the retrospective training cohort. Patients were excluded if no diagnostic, pre-operative MRI-images were available (minimum T1+Gadolinium and T2-weighed imaging), if survival data were unknown or no histological diagnosis was available. All patient records were reviewed considering patient and tumor characteristics, received treatments and survival data. The external validation cohort was constructed using the same criteria on an independent dataset of patients treated in Radboud University Medical Center  in the same time period. Both Maastricht UMC+ and Radboudumc are academic reference centers for GBM patients in the Netherlands, implying MRI-images were also obtained in hospitals that refer their patients to these academic centers. Numbers of patients used for each analysis are reported in Pre-operative MRI images were collected, pseudonymized and pooled in a database combining MRI images from different types and manufacturers of scanners using different imaging protocols to reflect the real-life inter-center heterogeneity . A quantUsing Osirix Lite  and MiM software , regions of interests (enhancing tumor on T1+Gadolinium images and combined tumor/edema portion on T2-weighted images) were manually delineated on all diagnostic MRI-images of the training and validation cohort, supervised by two experienced neuro-radiation oncologists .https://pypi.org/project/opencv-python/, (accessed on 23 December 2020)), SimpleITK version 1.2.0 ) and scikit-image version 0.14.2, ), an image pre-processing routine was developed to handle the broad variability of image acquisition and reconstruction parameters. Using Python 3.7 and the dedicated packages . The mode of the pixel spacing and slice thickness distributions from the Maastricht UMC+ cohort were used as reference values for the resampling procedure to minimize the number of resampled images. A bicubic interpolation over 4 × 4 pixel neighborhood was used for both upsampling and downsampling. In order to correct the low frequency intensity non-uniformity, which is intrinsic for MRI images, the N4 bias field correction algorithm was used [At first, spatial resolution of the images was normalized with respect to the image sequence  mutation (minimum coverage 500×) which was manually checked using Integrative Genomics Viewer (IGV). EGFR amplification was assessed using SNPitty, an open-source web application for interactive B-allele frequency and copy number visualization of NGS data, by comparing the number of reads in the EGFR locus to the surrounding regions [MGMT methylation status was assessed using methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) as previously described [IDH1 mutation status and EGFR amplification.Archival formalin-fixed paraffin-embedded (FFPE) tissue samples were analyzed for tumor percentage by an experienced neuro-pathologist (JB). DNA was extracted from FFPE tissue using the Cobas method  and DNA concentration was quantified using Qubit Fluorometer . Next-generation sequencing (NGS) was performed using the Ion AmpliSeq Cancer Hotspot Panel v2 (Life Technologies) as previously described . For the regions . MGMT meescribed . In caseStatistical analysis for differences between baseline characteristics was performed using double-sided T-test for “age at diagnosis”. Fisher’s exact test was used for all other binary variables .IDH-WT GBM samples.Overall survival (OS) was defined as the time between the initial surgical intervention after diagnosis and the date of death . Patients that survived were censored at the moment of the last follow-up measurement. To develop a prognostic model, analysis was focused on the p-value of ≤ 0.2 was considered for inclusion in the multivariable analysis. Resulting VASARI features were used for multivariable Cox-regression analysis with fast backward elimination  on the training set. Radiomics features from T1- and T2-weighted images were combined and normalized with the Z-score transformation, where coefficients evaluated on the train set were transferred to the validation set. Highly correlated features exceeding the Spearman’s rank correlation of rs = 0.85 were eliminated. Resulting radiomics features, were used for multivariable Cox-regression analysis with fast backward elimination for the training set [OS analysis was performed using R , employing the packages stats, survival, survminer, rms, pec and survcomp. VASARI features were tested in univariate Cox-regression analysis to determine the hazard ratio (HR) of each feature individually on the training cohort. Each feature with a ning set   curves were used with the threshold value based on 75th percentile of training PI’s in order to identify a high-risk group using our model. Significance of the split was estimated using the LR test. In addition, predicted survival curves for each risk group were plotted. The PI is used to estimate the survival curve, which is then averaged over the entire risk-group. These curves are plotted alongside the observed KM-curves. The correlation between radiomics features and tumor volume was assessed using Spearman’s rank correlation. This was investigated since previous studies have shown some radiomics features to be surrogate markers for tumor volume and not independent prognostic features . CorrelaPython 3.7 was used to develop and validate the predictive models. Patients with unknown outcomes (molecular markers) were excluded from the analysis. At first, highly correlated features (rs > 0.85) were eliminated, in which the feature with the lower AUC value in univariate ROC analysis was removed and resulting features were normalized using Z score on the MUMC+ cohort. Shift/scale parameters of individual features are available upon request. As the second step, the MUMC+ cohort was split randomly into train and test sets with a 70/30 ratio and label stratification. In the third step, to obtain the feature importance scores, a random forest model with the random-sampled initialization of hyper parameters , max depth ) was fitted 1000 times resulting in the cumulative feature importance histogram. Based on the feature importance rank, the 20 most important features were selected for the further evaluation. In order to find the best performing model in the fourth step, Xgboost, Random Forest and Logistic regression algorithms were initialized with the random-sampling of hyper parameters , trainedCombined model was achieved by ensembling VASARI and radiomics models using averaging of VASARI and radiomics predicted probabilities. To evaluate performance of the predictive models, the area under the receiver operating characteristic (ROC) curve, or AUC, was calculated. Bootstrapping technique with 100 iterations was utilized to estimate ROC AUC 95% confidence intervals on test and validation datasets.Additionally, to visualize the ability of radiomics features of capturing the outcome heterogeneity in a univariate manner and contribute to concept of explainable radiomics, we visualized the outcome heterogeneity through selected radiomics features by plotting the distribution of feature values for each particular feature of each binary outcome. The significance of the difference in the mean values was evaluated by performing the Mann–Whitney test with Bonferroni correction.To assess the quality of the conducted study, a radiomics quality score (RQS) was calculated. The RQS is a checklist consisting of 16 components to assess the validity of the radiomics workflow and  validation of the models ,80. FurtIn the present study, the potential of non-invasive quantitative and qualitative imaging features to predict prognosis and clinically relevant molecular markers was investigated in a real-life heterogeneous GBM patient cohort. The integrated prognostic model, including clinical and imaging features, showed the most promising performance which was reproducible and most robust between both datasets. However, further improvements and larger prospective studies are needed before this model can be used in daily clinical practice. Using imaging features to predict molecular markers showed promising results in the testing set but could not be validated on the external validation set and warrants additional validation in larger GBM cohorts.


The CRISPR/Cas system, particularly CRISPR/Cas9 , which are predominantly repaired via non-homologous end joining (NHEJ) or, to lesser extent, by homology-directed repair (HDR). The classical NHEJ repair pathway can generate small insertions or deletions (indels), resulting in loss-of-function of targeted coding genes by introducing a frameshift in the open reading frame (ORF). NHEJ mutagenesis is a highly popular strategy for gene manipulation. In addition to the classical NHEJ, alternative or accurate NHEJ-mediated repair can achieve precise genomic DNA deletions  is a well-established epigenetic modification on eukaryotic mRNA. An increasing number of studies have uncovered the significance of m6A methylation, which has given rise the nascent field of “epitranscriptomics.” Another article in this volume  describes a knock-out study in mouse spermatogonial GC-1 cells of the fat mass and obesity-associated (Fto) gene, which has been shown to act on the epitranscriptome as an m6A demethylase .On the other hand, the HDR repair pathway relies on homologous donor DNA to produce targeted gene knock-ins at the DSB site or gene replacement between two DSB sites. Precise point mutations and designed small indels can also be achieved by this method. One paper in this topic describes efforts to precisely correct the methyl-CpG binding protein 2 (MECP2) gene in the context of Rett syndrome (RTT) by CRISPR/Cas9-mediated HDR in human induced pluripotent stem cells (iPSCs). This report provides a reference for iPSC-based disease modeling and gene correction therapy . On the other hand, the HDR pathway can be also enhanced by the association of Cas9 with a variety of homologous recombination factors, such as yRad52 . A review paper in this topic  further summarizes the methodologies and other considerations for improving the HDR efficiency.It has been reported that inhibiting the key molecules of the competitive NHEJ pathway, such as DNA ligase IV (LIG4) and KU70, could improve the HDR efficiency effectively .Regarding biallelic targeting, we have previously reported a novel strategy using two donors with paired selectable markers     in this Research Topic report no obvious off-target events in the offspring of genetically edited goats. However, it remains to be determined as to whether these observations might be affected by survivorship bias, as well as differences in off-target events between human gene therapy and animal genetic breeding.The rapid development of genome editing technology has provided opportunities for modifying large animal models and domestic animal breeding. Pigs serve as an important agricultural resource as well as animal models for biomedical studies. In this topic, In conclusion, the articles contained within this Research Topic illustrate the mechanisms and great potential of precise genome editing techniques to further scientific inquiry and produce useful outcomes that benefit society.KX wrote the manuscript draft. DS and ZZ supervised the topic and read the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Background: In utero smoke (IUS) exposure is associated with asthma susceptibility. Objective: We sought to test the hypothesis that changes in miRNA expression by IUS exposure during human lung development is associated with asthma susceptibility. Methods: Gene expression was profiled from 53 IUS unexposed and 51 IUS exposed human fetal lung tissues. We tested for the differential expression of miRNAs across post-conception age and by IUS using linear models with covariate adjustment. We tested the IUS-associated miRNAs for association with their gene expression targets using pair-wise inverse correlation. Using our mouse model, we investigated the persistence of the IUS-associated miRNA signature using RT-PCR from the lungs of mouse pups with and without IUS at postnatal day 14. MiRNAs were then tested for association with asthma and exacerbations using whole blood gene expression profiles from Asthma BRIDGE. Results: Five miRNAs were differentially expressed across post-conception age (adjusted p < 0.0002) including two that were differentially expressed by IUS exposure in human fetal lung (p < 0.05). MiR-15a was differentially expressed by post-conception age (p = 0.00002), IUS exposure in human fetal lung (p = 0.005), and in the post-natal mouse lung (p = 0.01). MiR-15a was also associated with the in utero expression of GSDMB (adjusted p = 0.0002), a known childhood asthma gene and with asthma exacerbations (p = 0.0009) in Asthma BRIDGE. Thus, miR-15a is expressed during human lung development, is impacted by IUS exposure, regulates the intrauterine expression of asthma genes, and is associated with asthma severity. Conclusions: These results provide evidence for the role of miR-15a in the fetal origin of asthma. Asthma is characterized by airway inflammation, airway hyper-responsiveness, and reversible airflow obstruction. It is the most common chronic respiratory disease of childhood affecting 22 million people in the United States (U.S.), and is the most common cause of admissions to U.S. pediatric hospitals, and results in the highest number of missed school and work days each year in the U.S. ,2.Both genetic factors and environmental exposures have been shown to be involved in the pathogenesis of asthma. Substantial epidemiologic data supports a role for in utero smoke (IUS) exposure in the development of reduced lung function  and incrThe “fetal origins hypothesis”  proposesHuman lung development starts at approximately 4 weeks of gestation and can be classified into four distinct histologic stages: (1) pseudoglandular (weeks 7–17), (2) canalicular (weeks 17–26), (3) saccular (weeks 27–36), and (4) the alveolar (weeks 36–2 years) stages . We prevMicroRNAs (miRNAs) are small non-coding RNA molecules that modulate physiological and pathological processes by regulating gene expression at the post-transcriptional level by repressing translation or decreasing mRNA stability . Animal In our current work, we demonstrate the impact of IUS exposure on the miRNA signature of early human lung development. We identify miRNAs that are differentially expressed by IUS exposure during human lung development and demonstrate that these miRNAs regulate the intrauterine expression of known asthma susceptibility genes. Furthermore, we demonstrate that these developmental miRNAs are also associated with asthma severity in a well characterized asthma cohort, supporting an important role for developmental miRNAs in the pathogenesis of asthma later in life. Some of the results of these studies have been previously reported in the form of an abstract .Human fetal lung tissue samples were acquired through the tissue retrieval program sponsored by the National Institute of Child Health and Development, the University of Maryland Brain and Tissue Bank for Developmental Disorders , and the Center for Birth Defects Research  . Gene exRNA was extracted from fetal tissue whole lung homogenate and RNA sample quality was assessed using the Agilent 2100 Bioanalyzer . Genome-wide gene expression profiles were generated using the Affymetrix Human 1.0 ST Array. The pre-processing of the gene expression data was performed including background correction and quantile normalization prior to analysis. The probe with the highest variance for each miRNA was used as the representation of each miRNA. In total, ~200 of the known miRNAs were interrogated on this Affymetrix platform.We utilized our validated method to identify fetal lung tissues that had IUS exposure by measuring cotinine, a nicotine metabolite and established biomarker of tobacco smoke exposure, from the placental tissue corresponding to each of the human fetal lung tissues . IUS uneIn order to address the unmeasured confounders that exist in complex developmental gene expression data, a well-defined subset of samples was chosen for these analyses. Samples were matched based on age, gender, and principal components analysis (PCA) was used for outlier removal. PCA allows for matching based on variation in gene expression determined with measured and unmeasured variables. Samples matched for post-conception age and gender were then carried forward for differential expression.Differential miRNA expression across post-conception age was assessed using linear models adjusted for sex using the limma package in Bioconductor . In ordeThe developmentally regulated miRNAs were then tested for differential expression by IUS exposure using linear models adjusted for post-conception age and sex in limma . A strathttp://mirdb.org/miRDB/) using the genome-wide gene expression profiles for these samples. Pathway enrichment analysis of the gene expression targets was performed in DAVID [In order to determine whether developmentally regulated miRNAs that are differentially expressed by IUS exposure influence the intrauterine expression of known asthma genes, we next identified the gene expression (mRNA) targets of the IUS-associated miRNAs by comparing the inverse expression of the predicted mRNA target and the miRNAs in mirdb .Asthma BRIDGE is a multicenter-collaborative effort to develop translational genomic datasets for asthma in North America . SubjectDifferential miRNA expression analysis between IUS exposure status was assessed using linear models adjusted for age, sex, and race in limma . MiRNAs n = 53). Fifty-one samples that had placental cotinine values of ≥ 7.5 ng/g tissue represented the IUS exposed fetal lung tissue samples . There was a predominance of male subjects in both the IUS-unexposed and IUS-exposed samples.In total, 104 samples that were matched based on post-conception age and sex were included in the human fetal lung gene expression analysis of IUS exposure. The baseline characteristics of these samples are shown in p < 0.05 by post-conception age during human lung development (p = 0.009) during human fetal lung development. A stratified analysis between male and female samples was performed to identify sex-specific differences in miRNA expression across human lung development. Interestingly, three miRNAs were identified to be differentially expressed in male subjects, but not in female subjects,  and miR-15a (p = 0.003)  .GSDMB) [thymic stromal lymphopoietin (TSLP) [The gene targets of the two developmental miRNAs that were differentially expressed by IUS exposure during human fetal lung development include genes that have been previously associated with asthma susceptibility in published genome-wide association studies (GWAS) of asthma, including an association of miR-15a with Gasdermin B (GSDMB)  and miR-n (TSLP)  Table 4GSDMB [thn = 4) and without IUS (n = 4) exposure at postnatal day 14 (PN14). Although miR-155 was not significantly differentially expressed by IUS exposure in the postnatal period in our mouse model, we did confirm that IUS exposure results in a decreased miR-15a expression into the alveolar stage of development. We demonstrated that miR-15a is significantly differentially expressed between IUS-exposed and IUS-unexposed mouse lung at PN14  in asthma BRIDGE, miR-15a expression was noted to be associated with markers of asthma severity. Of note, miR-15a was significantly differentially expressed between asthmatics with and without asthma exacerbations (p = 0.052). Thus, additional investigations are necessary to determine the impact of microRNA expression on known asthma endotypes.Similar to the human fetal lung analysis, we found that miR-15a was differentially expressed by a history of IUS exposure in Asthma BRIDGE with higher levels of expression noted in the nonsmokers  regulate the intrauterine expression of known asthma susceptibility genes during human lung development. These results are consistent with recent studies that have shown that genetic variants associated with disease susceptibility in GWAS are more likely to regulate gene expression, and to be developmental genes . The genGSDMB  and TSLPMB [TSLP . NotablyTobacco smoke exposure has been previously shown to effect miRNA expression in the bronchial epithelium, with 28 miRNAs reported to be differentially expressed in current smokers compared to lifelong non-smokers  includinAlthough miR-15a has not been directly associated with asthma pathogenesis, a mouse model of graft versus host disease found that the over-expression of miR-15a in cord blood leads to the inhibition of the FOXP3 gene. Furthermore, miR-15a plays an important role in mediating the suppressive function of cord blood regulatory T cells (Tregs) . Foxp3 iPrevious studies of the role of miR-155 and miR-15a in human lung development, the role of IUS exposure on their expression patterns, and their association with the developmental origins of asthma are extremely limited. However, Rodriguez and colleagues have demonstrated that the knockout of miR-155 results in the development of an asthma-like phenotype including inflammatory cell infiltration into the airway and airway remodeling . FurtherNotably, our findings suggest that the impact of IUS exposure on microRNA expression differs from the effect of post-conception age alone. This is congruent to previously published developmental data demonstrating that the impact of IUS exposure changes across the developmental timeframe and that the effects may increase at later stages of gestation. The investigation of later developmental stages may help to elucidate these effects.Although we undertook a comprehensive analysis of the developmental signature of miRNAs and the influence of IUS exposure on this signature, several limitations of our analysis must be addressed. Although the Affymetrix array allows the interrogation of approximately 200 of the known miRNAs, this platform allows for only mature miRNA analysis and does not provide a more extensive investigation of novel and other known miRNAs. Furthermore, our analysis of human lung development is limited to fetal lung tissue samples from the early stages of development. Therefore, we were unable to investigate the miRNA profile during later human lung development. Since human fetal tissues from the later stages of gestation are difficult to obtain, we utilized our mouse model of IUS exposure to evaluate the later stages of development. Although we acknowledge that the investigation of miRNA expression patterns during the later stages of human lung development may allow us to gain further insights into the pathogenesis of respiratory diseases like asthma, the use of our mouse model allows for some additional insights regarding the miRNA expression changes that occur during the later stages of gestation and into the post-natal period. In addition, these results do suggest that the further investigation of these miRNAs as a biomarker of IUS exposure and asthma susceptibility and disease severity is warranted.In this study, we identified developmental miRNAs that are differentially expressed during early human lung development, impacted by IUS exposure, and influence the intrauterine expression of known asthma genes. In addition, we demonstrate that developmentally relevant miRNAs influence asthma severity in asthmatic patients. Our results do not only provide evidence for a role for miR-15a in the fetal origins of asthma, but should also motivate future investigations on the role of miRNAs in the pathogenesis of other respiratory diseases in which IUS exposure has been implicated in disease susceptibility.


Regulatory T cells (Tregs) are essential for the maintenance of tolerance to self and non-self through cell-intrinsic and cell-extrinsic mechanisms. Peripheral Tregs survival and clonal expansion largely depend on IL-2 and access to co-stimulatory signals such as CD28. Engagement of tumor necrosis factor receptor (TNFR) superfamily members, in particular TNFR2 and DR3, contribute to promote peripheral Tregs expansion and sustain their survival. This property can be leveraged to enhance tolerance to allogeneic transplants by tipping the balance of Tregs over conventional T cells during the course of immune reconstitution. This is of particular interest in peri-transplant tolerance induction protocols in which T cell depletion is applied to reduce the frequency of alloreactive T cells or in conditioning regimens that allow allogeneic bone marrow transplantation. These conditioning regimens are being implemented to limit long-term side effects of continuous immunosuppression and facilitate the establishment of a state of donor-specific tolerance. Lymphopenia-induced homeostatic proliferation in response to cytoreductive conditioning is a window of opportunity to enhance preferential expansion of Tregs during homeostatic proliferation that can be potentiated by agonist stimulation of TNFR. I. IkB sigApart from the predominant proinflammatory function of TNF, multiple sources support an anti-inflammatory role of this cytokine in chronic infections and in the chronic phase of many inflammatory diseases . One of In vitro studies of Tregs expansion in the presence of IL-2 and proinflammatory cytokines  have also contributed to gain insight into the role of TNF on Tregs function. Although some in vitro studies of Tregs exposure to TNF claimed that this cytokine interfered with Tregs suppressive function ,89, otheThe overall effect of TNF on Tregs seems to be mediated by signaling through TNFR2, which is highly expressed on both human and mouse Tregs when compared to conventional T cells ,76,91.The adoptive transfer of donor-derived Tregs to conditioned recipient mice attenuates the severity of graft-versus-host disease (GvHD) in different settings of allogeneic bone marrow transplantation across distinct MHC histocompatibility barriers ,93. Co-aIn the field of transplantation research, the most convincing data on the role of TNFR2 in Tregs expansion comes from three simultaneous studies in 2016 that took advantage of experimental mouse models of allogeneic bone marrow transplantation across distinct MHC barriers. In one of the studies, Chopra et al. developed a nonameric TNF complex with selective agonist activity on TNFR2, termed STAR2. This compound was composed of three covalently linked TNF trimers in which TNF monomers were mutated to selectively abrogate binding to TNFR1. They used this biological molecule to treat lethally irradiated recipients with the purpose to expand residual Tregs before performing allogeneic bone marrow transplantation across an MHC class I barrier A. This tIn solid organ transplantation, the number of studies is still scarce. It is worth mentioning one study that implicated TNF in chronic rejection of heart allografts . One of In conclusion, these data point to the fact that TNFR2 is a promising targetable molecule for the expansion of donor or recipient Tregs that display functional suppressive activity to modulate the course of GvHD across distinct histocompatibility barriers and to mitigate the process of chronic rejection of vascularized allografts.The TNFRSF member termed death receptor 3  is a type I transmembrane protein with homology to TNFR1 . DR3 engDR3 (TNFRSF25) was initially claimed to be preferentially expressed on Tregs and only barely on resting T cells . This noThe expansion of Tregs upon DR3 engagement was first described in a mouse model of allergy. In this model, the administration of anti-DR3 agonist antibody (clone 4C12) or soluble TL1A.Ig recombinant fusion protein (soluble DR3 agonist) stimulated a transient expansion of Tregs. This agonist activity was modestly increased by the addition of IL-2 immunocomplexes (IL-2/anti-IL-2) .Taking advantage of the knowledge gathered from mouse models of allergy, in vivo expansion of donor Tregs with agonist anti-DR3 antibody was achieved before bone marrow cells were harvested for the transplant. This intervention permits the enrichment of donor Tregs in the bone marrow inoculum that would contribute to mitigate the pathogenic impact of donor anti-host alloreactivity . The exp+ to 30–35% of gated CD4+ cells. This increase in Tregs was associated with a significant graft prolongation from day 8 to day 17 that correlated with accumulation of Foxp3+ Tregs within the graft and a significant reduction of infiltrating inflammatory cells [In the setting of heart allogeneic transplantation, treatment with agonist anti-DR3 antibody (clone 4C12) resulted in expansion of Tregs Foxp3ry cells .In summary, DR3 is a targetable receptor that permits the preferential expansion of donor Tregs or residual host Tregs that remain after host conditioning. Anti-DR3 treatment should be implemented before donor anti-host alloreactive T cells become activated.Etanercept (TNF decoy receptor) and infliximab (chimeric anti-TNF antibody) are two examples of the most common TNF blockers approved for clinical use as a second line for the treatment of steroid-refractory GvHD and autoimmune diseases either alone or in combination with methotrexate; however, some patients do not respond, and disease can be exacerbated upon TNF blockade. This undesirable outcome may be the result of inhibition of Tregs suppressive function that prevents membrane-bound TNF binding to TNFR2.To overcome these hurdles, there is an emerging interest in the development of recombinant biological compounds that can target specifically TNFR2 without engaging TNFR1, to expand in vivo Tregs and potentiate their beneficial modulatory effect on the course of inflammation ,107. ConOne consideration that should be kept in mind arises from the fact that T cell activation upregulates most TNFR members in both Tregs and conventional T cells, and the engagement of these receptors can contribute to co-stimulation. This co-signal effect would enhance T cell cytotoxic activity or would make effector T cells more resistant to Tregs-mediated suppression . A sense


Increased Coulomb repulsion from surface states substantially modulates quantum confinement in topological semimetal nanofilms. The emergence of quantization at the nanoscale, the quantum size effect (QSE), allows flexible control of matter and is a rich source of advanced functionalities. A QSE-induced transition into an insulating phase in semimetallic nanofilms was predicted for bismuth a half-century ago and has regained new interest with regard to its surface states exhibiting nontrivial electronic topology. Here, we reveal an unexpected mechanism of the transition by high-resolution angle-resolved photoelectron spectroscopy combined with theoretical calculations. Anomalous evolution and degeneracy of quantized energy levels indicate that increased Coulomb repulsion from the surface states deforms a quantum confinement potential with decreasing thickness. The potential deformation strongly modulates spatial distributions of quantized wave functions, which leads to acceleration of the transition beyond the original QSE picture. This discovery establishes a complete picture of the long-discussed transition and highlights a new class of size effects dominating nanoscale transport in systems with metallic surface states. EF), and the system enters an insulating phase. In the case of a system having metallic surface states as typically observed in topological materials, the transition is marked by the disappearance of conducting channels in the film interior, and thereafter, electric current flows only through the surfaces.Quantized electronic states generated by the quantum size effect (QSE) in nano-confined systems enable unique tunability for a wide range of phenomena such as superconductivity   that havEF in atomically thin regions  calculations reveal that the level degeneracy is gradually induced by shifting the whole band structure and accompanies transformation of the bulk-derived wave functions into surface-localized ones. This tendency is totally opposite to a well-known hybridization effect between top and bottom surface states and reconciles the contradiction among the previous experiments in an unprecedented manner. These unusual modulations of quantized bulk states can be fully explained only when we consider deformation of a quantum confinement potential, which is triggered by enhanced effects of Coulomb repulsion with decreasing system size, centering on a size-independent contribution from the surface states. The present study not only solves the serious controversy on the transition discussed for half a century but also introduces the novel size effect that can be universally present in a system with metallic surface states, typically topological materials.EF in atomically thin films. This contrasts with the previous ARPES result . As far as we know, this is the first direct observation of a metal-insulator transition with all the related electronic states resolved on a thin-film system that exhibits macroscopically insulating transport. The situation is in clear contrast to studies on atomically thin films of bulk-conducting topological insulators  at EF, as highlighted by shaded bars in Therefore, a plot of quantized energy levels versus inverse thicknesses depicts a bulk band dispersion perpendicular to the film surface. At on of Bi . Figure n = 1 and 2 quantized levels are almost degenerate . In the one-body picture of the DFT framework, the compressed total charge distribution, in turn, makes an electron feel a potential barrier around the film center and deforms Thus, the two essential signatures here, the degeneracy between the top two quantized bulk states and their transformation into surface-localized states, rule out scenarios given by any standard mechanism but are naturally explained by considering the deformation of a quantum confinement potential via Coulomb repulsion from the surface states. One of the most interesting points is that a usually weak effect of Coulomb repulsion and hybridization between the surface and quantized bulk states are enhanced with decreasing system size centering on the presence of the surface states.EF (see fig. S3C). Nevertheless, as shown in We revisit the strange contradiction among recent studies on the metal-insulator transition in Bi films. The central problem is a metallic envelope of quantized bulk states captured by the previous ARPES of atomically thin Bi films grown on a Si(111) substrate  wafer cleaned by cycles of Ar+ sputtering and annealing at 900 K. Bi evaporation was performed at room temperature, followed by annealing at 400 K (Bi(111) films were grown epitaxially on a medium-doped at 400 K  with the−9 Pa. The measurement direction was precisely adjusted using an automated six-axis rotational controller and was based on Fermi surfaces that were mapped before every band structure scan. To directly determine unoccupied band structures, we also performed alkali-metal adsorption following an approach in (High-resolution ARPES measurements were performed at BL-9A of the Hiroshima Synchrotron Radiation Center (HSRC) and BL-21B1 of the National Synchrotron Radiation Research Center (NSRRC). At BL-9A, a high-intensity unpolarized Xe plasma discharge lamp (8.437 eV) was used for magnifying small energy ranges, in addition to the synchrotron radiation (21 eV) for wide-range observations. The measurement temperature was 10 K, and the total energy resolution was 7 meV for 8.437-eV photons and 12 meV for 21-eV photons. The pressure during the measurements was 10sp3 orbitals between first, second, and third nearest-neighbor atoms with spin-orbit coupling implemented. Electronic structures in a slab geometry were calculated by extending the bulk matrix to a larger 16N × 16N matrix, where N is the number of bilayers, as demonstrated in (Tight-binding calculations for bulk electronic structures of Bi were based on a framework introduced in (k-point sampling as 9 × 9 × 1 was used. Convergences with respect to an energy cutoff, the k-point sampling, and the vacuum length were confirmed for obtained band structures. We also cross-checked the results using the QUANTUM ESPRESSO code (DFT calculations (L is a maximum length scale of the simulation (A numerical simulation was performed using a 1D Schrödinger equation with an electron mass extracted from the tight-binding band structure. Eigenvalues were calculated by taking the Fourier transform of a wave function