Ginsenoside Rg1 Nanoparticles Induce Demethylation of H3K27me3 in VEGF-A and Jagged 1 Promoter Regions to Activate Angiogenesis After Ischemic Stroke

BACKGROUND

Compared with traditional drugs, nanomaterial drugs have the benefits of improving the solubility, bioavailability, and absorption rate of insoluble drugs. Nanoporous complexes can increase the efficiency with which drugs can penetrate the blood-brain barrier and reach target organs. Ginsenoside Rg1 is an effective drug that promotes angiogenesis. Ginsenoside Rg1 composite nanoparticles were employed to induce the expression of several key epigenetic enzymes and then activate the VEGF and Notch pathways after the onset of ischemic brain lesions.

METHODS

We constructed nanoparticles to fully encapsulate the therapeutic drug (ginsenoside Rg1), which can be transferred into brain tissue via the receptor-mediated transfer of drug-encapsulated nanoparticles. Evaluation of the therapeutic effect of ginsenoside Rg1 complex nanovesicles (CNV) was performed by in vitro and in vivo experiments. Real-time polymerase chain reaction (RT- PCR), Western blot, immunohistochemistry staining (IHC), and Co-immunoprecipitation (co-IP) were employed to screen for epigenetic enzymes with an up-regulated expression post ginsenoside Rg1-CNV intervention. RNA sequencing, shRNA knockdown, and chromatin Immunoprecipitation (ChIP) sequencing were performed to detect the target genes of ginsenoside Rg1-CNV that regulate angiogenesis. Then, bioinformatic analysis was performed to investigate the mechanism of action of epigenetic modifying enzymes in regulating target genes.

RESULTS

The average of the synthesized ginsenoside Rg1-CNV was 203.78±6.83 nm, the polydispersion index was 0.135±0.007, and the Zeta potential was 23.13±1.65 mV. Through in vivo and in vitro experiments, we found that it promotes the proliferation, migration, and tubular formation of brain microvascular endothelial cells (BMECs). Meanwhile, the intervention of ginsenoside Rg1-CNV promoted the demethylation of H3K27me3 within the promoter region of VEGF-A and Jagged1 genes and reduced the H3K27me3 modification within this region.

CONCLUSION

The ginsenoside Rg1 nanoparticles may be an available blood-brain barrier penetrating agent for ischemic stroke.

A, Barbano A, Barwick SW, Bastian B, Basu V, Baur S, Bay R, Beatty JJ, Becker KH, Becker Tjus J, Bellenghi C, BenZvi S, Berley D, Bernardini E, Besson DZ, Binder G, Bindig D, Blaufuss E, Blot S, Boddenberg M, Bontempo F, Borowka J, Böser S, Botner O, Böttcher J, Bourbeau E, Bradascio F, Braun J, Brinson B, Bron S, Brostean-Kaiser J, Browne S, Burgman A, Burley RT, Busse RS, Campana MA, Carnie-Bronca EG, Chen C, Chen Z, Chirkin D, Choi K, Clark BA, Clark K, Classen L, Coleman A, Collin GH, Conrad JM, Coppin P, Correa P, Cowen DF, Cross R, Dappen C, Dave P, De Clercq C, DeLaunay JJ, Delgado López D, Dembinski H, Deoskar K, Desai A, Desiati P, de Vries KD, de Wasseige G, de With M, DeYoung T, Diaz A, Díaz-Vélez JC, Dittmer M, Dujmovic H, Dunkman M, DuVernois MA, Dvorak E, Ehrhardt T, Eller P, Engel R, Erpenbeck H, Evans J, Evenson PA, Fan KL, Fazely AR, Fedynitch A, Feigl N, Fiedlschuster S, Fienberg AT, Filimonov K, Finley C, Fischer L, Fox D, Franckowiak A, Friedman E, Fritz A, Fürst P, Gaisser TK, Gallagher J, Ganster E, Garcia A, Garrappa S, Gerhardt L, Ghadimi A, Glaser C, Glauch T, Glüsenkamp T, Goldschmidt A, Gonzalez JG, Goswami S, Grant D, Grégoire T, Griswold S, Günther C, Gutjahr P, Haack C, Hallgren A, Halliday R, Halve L, Halzen F, Ha Minh M, Hanson K, Hardin J, Harnisch AA, Haungs A, Hebecker D, Helbing K, Henningsen F, Hettinger EC, Hickford S, Hignight J, Hill C, Hill GC, Hoffman KD, Hoffmann R, Hokanson-Fasig B, Hoshina K, Huang F, Huber M, Huber T, Hultqvist K, Hünnefeld M, Hussain R, Hymon K, In S, Iovine N, Ishihara A, Jansson M, Japaridze GS, Jeong M, Jin M, Jones BJP, Kang D, Kang W, Kang X, Kappes A, Kappesser D, Kardum L, Karg T, Karl M, Karle A, Katz U, Kauer M, Kellermann M, Kelley JL, Kheirandish A, Kin K, Kintscher T, Kiryluk J, Klein SR, Koirala R, Kolanoski H, Kontrimas T, Köpke L, Kopper C, Kopper S, Koskinen DJ, Koundal P, Kovacevich M, Kowalski M, Kozynets T, Kun E, Kurahashi N, Lad N, Lagunas Gualda C, Lanfranchi JL, Larson MJ, Lauber F, Lazar JP, Lee JW, Leonard K, Leszczyńska A, Li Y, Lincetto M, Liu QR, Liubarska M, Lohfink E, Lozano Mariscal CJ, Lu L, Lucarelli F, Ludwig A, Luszczak W, Lyu Y, Ma WY, Madsen J, Mahn KBM, Makino Y, Mancina S, Mariş IC, Martinez-Soler I, Maruyama R, Mase K, McElroy T, McNally F, Mead JV, Meagher K, Mechbal S, Medina A, Meier M, Meighen-Berger S, Micallef J, Mockler D, Montaruli T, Moore RW, Morse R, Moulai M, Naab R, Nagai R, Nahnhauer R, Naumann U, Necker J, Nguyen LV, Niederhausen H, Nisa MU, Nowicki SC, Nygren D, Obertacke Pollmann A, Oehler M, Oeyen B, Olivas A, O’Sullivan E, Pandya H, Pankova DV, Park N, Parker GK, Paudel EN, Paul L, Pérez de los Heros C, Peters L, Peterson J, Philippen S, Pieper S, Pittermann M, Pizzuto A, Plum M, Popovych Y, Porcelli A, Prado Rodriguez M, Price PB, Pries B, Przybylski GT, Raab C, Rack-Helleis J, Raissi A, Rameez M, Rawlins K, Rea IC, Rehman A, Reichherzer P, Reimann R, Renzi G, Resconi E, Reusch S, Rhode W, Richman M, Riedel B, Roberts EJ, Robertson S, Roellinghoff G, Rongen M, Rott C, Ruhe T, Ryckbosch D, Rysewyk Cantu D, Safa I, Saffer J, Sanchez Herrera SE, Sandrock A, Sandroos J, Santander M, Sarkar S, Sarkar S, Satalecka K, Schaufel M, Schieler H, Schindler S, Schmidt T, Schneider A, Schneider J, Schröder FG, Schumacher L, Schwefer G, Sclafani S, Seckel D, Seunarine S, Sharma A, Shefali S, Silva M, Skrzypek B, Smithers B, Snihur R, Soedingrekso J, Soldin D, Spannfellner C, Spiczak GM, Spiering C, Stachurska J, Stamatikos M, Stanev T, Stein R, Stettner J, Steuer A, Stezelberger T, Stokstad R, Stürwald T, Stuttard T, Sullivan GW, Taboada I, Ter-Antonyan S, Tilav S, Tischbein F, Tollefson K, Tönnis C, Toscano S, Tosi D, Trettin A, Tselengidou M, Tung CF, Turcati A, Turcotte R, Turley CF, Twagirayezu JP, Ty B, Unland Elorrieta MA, Valtonen-Mattila N, Vandenbroucke J, van Eijndhoven N, Vannerom D, van Santen J, Verpoest S, Walck C, Watson TB, Weaver C, Weigel P, Weindl A, Weiss MJ, Weldert J, Wendt C, Werthebach J, Weyrauch M, Whitehorn N, Wiebusch CH, Williams DR, Wolf M, Woschnagg K, Wrede G, Wulff J, Xu XW, Yanez JP, Yoshida S, Yu S, Yuan T, Zhang Z, Zhelnin P. Evidence for neutrino emission from the nearby active galaxy NGC 1068

A supermassive black hole, obscured by cosmic dust, powers the nearby active galaxy NGC 1068. Neutrinos, which rarely interact with matter, could provide information on the galaxy’s active core. We searched for neutrino emission from astrophysical objects using data recorded with the IceCube neutrino detector between 2011 and 2020. The positions of 110 known gamma-ray sources were individually searched for neutrino detections above atmospheric and cosmic backgrounds. We found that NGC 1068 has an excess of 79 − 20 + 22 neutrinos at tera–electron volt energies, with a global significance of 4.2σ, which we interpret as associated with the active galaxy. The flux of high-energy neutrinos that we measured from NGC 1068 is more than an order of magnitude higher than the upper limit on emissions of tera–electron volt gamma rays from this source.

Comprehensive and clinically accurate head and neck cancer organs-at-risk delineation on a multi-institutional study

Accurate organ-at-risk (OAR) segmentation is critical to reduce radiotherapy complications. Consensus guidelines recommend delineating over 40 OARs in the head-and-neck (H&N). However, prohibitive labor costs cause most institutions to delineate a substantially smaller subset of OARs, neglecting the dose distributions of other OARs. Here, we present an automated and highly effective stratified OAR segmentation (SOARS) system using deep learning that precisely delineates a comprehensive set of 42 H&N OARs. We train SOARS using 176 patients from an internal institution and independently evaluate it on 1327 external patients across six different institutions. It consistently outperforms other state-of-the-art methods by at least 3-5% in Dice score for each institutional evaluation (up to 36% relative distance error reduction). Crucially, multi-user studies demonstrate that 98% of SOARS predictions need only minor or no revisions to achieve clinical acceptance (reducing workloads by 90%). Moreover, segmentation and dosimetric accuracy are within or smaller than the inter-user variation.

Search for Unstable Sterile Neutrinos with the IceCube Neutrino Observatory

We present a search for an unstable sterile neutrino by looking for a resonant signal in eight years of atmospheric ν_{μ} data collected from 2011 to 2019 at the IceCube Neutrino Observatory. Both the (stable) three-neutrino and the 3+1 sterile neutrino models are disfavored relative to the unstable sterile neutrino model, though with p values of 2.8% and 0.81%, respectively, we do not observe evidence for 3+1 neutrinos with neutrino decay. The best-fit parameters for the sterile neutrino with decay model from this study are Δm_{41}^{2}=6.7_{-2.5}^{+3.9}  eV^{2}, sin^{2}2θ_{24}=0.33_{-0.17}^{+0.20}, and g^{2}=2.5π±1.5π, where g is the decay-mediating coupling. The preferred regions of the 3+1+decay model from short-baseline oscillation searches are excluded at 90% C.L.

SAM: Self-Supervised Learning of Pixel-Wise Anatomical Embeddings in Radiological Images

Radiological images such as computed tomography (CT) and X-rays render anatomy with intrinsic structures. Being able to reliably locate the same anatomical structure across varying images is a fundamental task in medical image analysis. In principle it is possible to use landmark detection or semantic segmentation for this task, but to work well these require large numbers of labeled data for each anatomical structure and sub-structure of interest. A more universal approach would learn the intrinsic structure from unlabeled images. We introduce such an approach, called Self-supervised Anatomical eMbedding (SAM). SAM generates semantic embeddings for each image pixel that describes its anatomical location or body part. To produce such embeddings, we propose a pixel-level contrastive learning framework. A coarse-to-fine strategy ensures both global and local anatomical information are encoded. Negative sample selection strategies are designed to enhance the embedding's discriminability. Using SAM, one can label any point of interest on a template image and then locate the same body part in other images by simple nearest neighbor searching. We demonstrate the effectiveness of SAM in multiple tasks with 2D and 3D image modalities. On a chest CT dataset with 19 landmarks, SAM outperforms widely-used registration algorithms while only taking 0.23 seconds for inference. On two X-ray datasets, SAM, with only one labeled template image, surpasses supervised methods trained on 50 labeled images. We also apply SAM on whole-body follow-up lesion matching in CT and obtain an accuracy of 91%. SAM can also be applied for improving image registration and initializing CNN weights.

[Analysis on the epidemic characteristics and genetic characteristics of varicella in Beijing from 2019 to 2021]

The reported incidence of varicella in Beijing from 2019 to 2021 were 63.8/100 000, 32.2/100 000 and 38.6/100 000, respectively. There were two VZV epidemics in Beijing each year, one peaked in May and the other in November. However, the first VZV epidemic almost disappeared in 2020. Among the cases involved in the varicella outbreaks in school, the proportion of the students with no history of vaccine immunization, 1 dose of immunization and 2 doses of immunization were 33.12%, 44.79% and 22.08%, respectively. The major body of VZV breakthrough cases was children aged 6-14 years (523/755, 69.27%). The proportion of moderate- or severe-rash were 55.32%, 39.06%, 29.96% in the three groups of cases with no immunization history, 1 dose of immunization and 2 doses of immunization, respectively (P<0.001). A total of 1 089 varicella samples were collected, and 837 (76.86%) were confirmed to be PCR-positive for VZV and were identified as VZV wild strains. 311 VZV strains were sequenced successfully, and 307 strains were clade 2 (98.72%), 1 clade 3 (0.32%) and 3 Clade 5 (0.96%). Compared with the representative strains, the nucleotide similarities of ORF22 fragments were between 99.4% and 100%, and amino acid similarities were between 99.4% and 100%.

A flexible three‐dimensional heterophase computed tomography hepatocellular carcinoma detection algorithm for generalizable and practical screening

Hepatocellular carcinoma (HCC) can be potentially discovered from abdominal computed tomography (CT) studies under varied clinical scenarios (e.g., fully dynamic contrast‐enhanced [DCE] studies, noncontrast [NC] plus venous phase [VP] abdominal studies, or NC‐only studies). Each scenario presents its own clinical challenges that could benefit from computer‐aided detection (CADe) tools. We investigate whether a single CADe model can be made flexible enough to handle different contrast protocols and whether this flexibility imparts performance gains. We developed a flexible three‐dimensional deep algorithm, called heterophase volumetric detection (HPVD), that can accept any combination of contrast‐phase inputs with adjustable sensitivity depending on the clinical purpose. We trained HPVD on 771 DCE CT scans to detect HCCs and evaluated it on 164 positives and 206 controls. We compared performance against six clinical readers, including two radiologists, two hepatopancreaticobiliary surgeons, and two hepatologists. The area under the curve of the localization receiver operating characteristic for NC‐only, NC plus VP, and full DCE CT yielded 0.71 (95% confidence interval [CI], 0.64–0.77), 0.81 (95% CI, 0.75–0.87), and 0.89 (95% CI, 0.84–0.93), respectively. At a high‐sensitivity operating point of 80% on DCE CT, HPVD achieved 97% specificity, which is comparable to measured physician performance. We also demonstrated performance improvements over more typical and less flexible nonheterophase detectors. Conclusion: A single deep‐learning algorithm can be effectively applied to diverse HCC detection clinical scenarios, indicating that HPVD could serve as a useful clinical aid for at‐risk and opportunistic HCC surveillance.

Preferential reporting of significant p-values in radiology journal abstracts

AIM

To assess the prevalence of publication bias in the radiology literature, data-mining techniques were used to extract p-values in abstracts published in key radiology journals over the past 20 years.

MATERIALS AND METHODS

A total of 34,699 abstracts published in Radiology, Investigative Radiology, European Radiology, American Journal of Roentgenology, and American Journal of Neuroradiology published between January 2000 and December 2019 were included in the analysis. Automated text mining using regular expressions was used to mine abstracts for p-values.

RESULTS

The text mining algorithm detected 43,489 p-values, the majority (82.4%) of which were reported as "significant", i.e., p<0.05. There has also been an increased propensity to report more p-values over time. The distribution of p-values showed a step change at the conventional significance threshold of 0.05. The odds ratio of a "significant" p-value being reported in the abstract compared to the full text was calculated to be 2.52 (95% confidence interval 1.78-3.58; p<0.001). Taken together, these results provide strong evidence for selective reporting of significant p-values in abstracts.

CONCLUSION

Statistically significant p-values are preferentially reported in radiology journal abstracts.

[Heritability and genetic correlation of body mass index and coronary heart disease in Chinese adult twins]

Objective: To examine the heritability of body mass index (BMI) and coronary heart disease (CHD), and to explore whether genetic factors can explain their correlation. Methods: Participants were from 11 provinces/municipalities reqistered in the Chinese National Twin Registry (CNTR) from 2010 to 2018. Participants data were collected from face-to-face questionnaire survey. Bivariate structure equation model was used to estimate the heritability and the genetic correlation of BMI and CHD. Results: A total of 20 340 pairs of same-sex twins aged ≥25 years were included in this study. After adjusting for age and gender, the heritability of BMI and CHD was 0.52 (95%CI: 0.49-0.55) and 0.76 (95%CI: 0.69-0.81), respectively. Further, a genetic correlation was identified between BMI and CHD (r_A=0.10, 95%CI:0.02-0.17). Conclusion: In Chinese adult twin population, BMI and CHD are affected by genetic factors, and their correlation can be attributed to the common genetic basis.

Strong Constraints on Neutrino Nonstandard Interactions from TeV-Scale ν_{μ} Disappearance at IceCube

We report a search for nonstandard neutrino interactions (NSI) using eight years of TeV-scale atmospheric muon neutrino data from the IceCube Neutrino Observatory. By reconstructing incident energies and zenith angles for atmospheric neutrino events, this analysis presents unified confidence intervals for the NSI parameter ε_{μτ}. The best-fit value is consistent with no NSI at a p value of 25.2%. With a 90% confidence interval of -0.0041≤ε_{μτ}≤0.0031 along the real axis and similar strength in the complex plane, this result is the strongest constraint on any NSI parameter from any oscillation channel to date.