N-(4-chlorophenyl) substituted pyranopyrazoles was synthesised and screened for their potential to inhibit kinases and exhibit anticancer activity against primary patient-derived glioblastoma 2D cells and 3D neurospheres. A collection of 10 compounds was evaluated against glioma cell lines, with compound 4j exhibiting promising glioma growth inhibitory properties. Compound 4j was screened against 139 purified kinases and exhibited low micromolar activity against kinase AKT2/PKBβ. AKT signalling is one of the main oncogenic pathways in glioma and is often targeted for novel therapeutics. Indeed, AKT2 levels correlated with glioma malignancy and poorer patient survival. Compound 4j inhibited the 3D neurosphere formation in primary patient-derived glioma stem cells and exhibited potent EC50 against glioblastoma cell lines. Although exhibiting potency against glioma cells, 4j exhibited significantly less cytotoxicity against non-cancerous cells even at fourfold–fivefold the concentration. Herein we establish a novel biochemical kinase inhibitory function for N-(4-chlorophenyl) substituted pyranopyrazoles and further report their anti-glioma activity in vitro for the first time.4j inhibited the 3D neurosphere formation in primary patient-derived glioma stem cells. 4j also displayed PKBβ/AKT2 inhibitory activity. 4j is nontoxic towards non-cancerous cells.Anti-glioma pyranopyrazole A series of  In addiBiologically potent pyranopyrazoles synthesised by two-component, three-component, and four-component synthesises have been reported previously  17]. A . A 17]. N-(4-chlorophenyl) substituted pyranopyrazoles. DABCO is a highly reactive, inexpensive, eco-friendly, nontoxic catalyst for various organic transformations pyrazoles by aldehyde based DABCO catalysed three-component reaction  by three-component reaction of aldehyde 1, 1-(4-chlorophenyl)-3-methyl-5-pyrazolone 2 and malononitrile 3 , 159.34 (C-6), 145.74 (C-7a), 98.89 (C-3a) ppm. The signal of nitrile carbon appeared at δ 119.93 ppm. Eight signals that appeared in the range δ 121.37–143.48 ppm confirmed the presence of aromatic carbons. The same pattern of signals was observed in 13C{1H}-NMR of other synthesised products. Some deviation in the position of signals was observed due to the effect of a substituted functional group at the fourth position of phenyl ring substituted in pyran ring.All synthesised pyranopyrazoles are characterised by mass spectrometry. The molecular ion peak was observed in HRMS of each synthesised compound matched with its calculated value.2.2.2.2.1.in vitro, EC50 values were conducted on all synthesised compounds in triplicates against murine glioblastoma cell line GL261. Out of the 10 molecules tested, 4j had the lowest EC50 value of 20 μM  values of compounds 4a–4j in GL261 cells in vitro.To determine the biological relevance of these molecules of 20 μM . Potent 2.2.2.4j, 5 μM 4j was screened over 139 purified kinases at the International Centre for Protein Kinase Profiling, University of Dundee, UK. Interestingly, 4j significantly inhibited PKBβ/AKT2 with a high degree of specificity  have the highest AKT2 mRNA expression along with the lowest overall survival . To unde2.2.4.4j, we utilised immortalised murine glioblastoma cell line GL261 along with primary patient-derived xenograft cells  and glioblastoma stem 3D neurospheres . The cell lines and accompanying de-identified histopathological information were established at the Mayo Clinic Brain Tumour PDX National Resource, USA. All three patient-derived primary glioma samples were IDH1 wild-type with in vivo bilateral invasive structures observed via neuropathology. The effect of 4j on cell viability was measured against GL261, GBM6, and GBM22 cell lines. After 72 h incubation, cell viability was measured, and the EC50 values for 4j in GL261 are approximately 20 μM and 30 μM in GBM6 and GBM22  or BV2 (murine) with modest but statistically significant cell death observed in human embryonic kidney HEK293T cells at high 100 μM dose  substituted pyranopyrazole derivatives was synthesised , this sere size  and 3D gis 12 nM , which implified . Furtherey cells  which sut 100 μM . It is a4.4.1.4.1.1.1H and 13C{1H} NMR spectra were recorded on a Bruker AV-400 or Bruker AV-600 device. Chemical shifts are expressed in ppm relative to TMS in DMSO-d6. High-resolution mass spectra were obtained on a Bruker Compass Data Analysis 4.0 spectrometer. Pyranopyrazoles with labelled atoms are shown in Supporting Information Figures S2–S32.We purchased 1,4 Diazabicyclo[2.2.2]octane (DABCO) from Alfa Aesar Chemical Company. 4-Ethoxy benzaldehyde, 4-phenyl benzaldehyde and 1-(4-chlorophenyl)-3-methyl-5-pyrazalone were purchased from TCI Chemicals (India) Pvt. Ltd. Benzaldehyde, p-tolualdehyde, 4-nitro benzaldehyde, 4-chloro benzaldehyde, and 4-hydroxy benzaldehyde were purchased from Sisco Research Laboratories Pvt. Ltd. 4-Bromo benzaldehyde and 4-fluoro benzaldehyde were purchased from Spectrochem Pvt. Ltd. 4.1.2.In a round bottom flask, 1 mmol aldehyde, 1 mmol 1-(4-chlorophenyl)-3-methyl-5-pyrazolone, 1.1 mmol malononitrile and 0.1 mmol DABCO were mixed in 5 mL ethanol. The reaction mixture was refluxed and stirred at 78 °C for 30 min in a water bath. The water bath temperature should be below 80 °C; otherwise, it caused the reaction mixture to become more brownish, which increases effort in the workup process. In case the reaction mixture solidified, extra 3 mL ethanol was added. The progress of the reaction was monitored by TLC (hexane/ethyl acetate = 1/1). After completion, the reaction mixture was cooled to room temperature and filtered to separate the product. The product was washed with warm water three times to remove colour impurity.4.1.2.1.1H NMR  δ: 1.78 , 4.68 , 7.26–7.28 , 7.35, 7.54 , 7.83 ; 13C{1H} NMR  δ: 12.6 (CH3), 36.7 (CH), 58.2 (C-5), 98.9(C-3a), 119.9 (CN), 121.4 (Ar-C), 127.1 (Ar-C), 127.8 (Ar-C), 128.5 (Ar-C), 129.2 (Ar-C), 130.2 (Ar-C), 136.4 (Ar-C), 143.5 (Ar-C), 144.0 (C-3), 145.7 (C-7a), 159.3 (C-6); HRMS (ESI-TOF) m/z calcd. for C20H15ClN4O (M + H)+: 363.10126, found: 363.10024.White solid , mp: 196–198 °C; 4.1.2.2.1H NMR  δ: 1.78 , 2.29 , 4.62 , 7.14 , 7.23 , 7.53 , 7.83 ; 13C{1H} NMR  δ: 12.6 (CH3), 20.7(CH3), 36.3 (CH), 58.4 (C-5), 99.0(C-3a), 119.9 (CN), 121.3 (Ar-C), 127.7 (Ar-C), 129.1 (Ar-C), 129.2 (Ar-C), 130.1 (Ar-C), 136.1 (Ar-C), 136.4 (Ar-C), 140.5 (Ar-C), 143.9(C-3), 145.8 (C-7a), 159.2(C-6); HRMS (ESI-TOF) m/z calcd. for C21H17ClN4O (M + H)+: 377.11691, found: 377.11585.White solid , mp: 210–212 °C; 4.1.2.3.1H NMR  δ: 1.79 , 4.93 , 7.42 , 7.57 , 7.84 , 8.23 ; 13C{1H} NMR  δ: 12.6 (CH3), 36.3 (CH), 56.9 (C-5), 97.8(C-3a), 119.7 (CN), 121.5 (Ar-C), 123.9 (Ar-C), 129.2 (Ar-C), 130.4 (Ar-C), 136.3 (Ar-C), 144.1(C-3), 145.6 (C-7a), 146.6 (Ar-C), 151.1 (Ar-C), 159.6(C-6); HRMS (ESI-TOF) m/z calcd. for C20H14ClN5O3 (M + H)+: 408.08634, found: 408.08520.Light yellow solid , mp: 228–230 °C; 4.1.2.4.1H NMR  δ: 1.79 , 4.73 , 7.30–7.32 , 7.41 , 7.54 , 7.83 ; 13C{1H} NMR  δ: 12.6 (CH3), 36.0 (CH), 57.7 (C-5), 98.4(C-3a), 119.8 (CN), 121.4 (Ar-C), 128.5 (Ar-C), 129.2 (Ar-C), 129.7 (Ar-C), 130.3 (Ar-C), 131.6 (Ar-C), 136.3 (Ar-C), 142.6 (Ar-C), 144.0 (C-3), 145.7 (C-7a), 159.4(C-6); HRMS (ESI-TOF) m/z calcd. for C20H14Cl2N4O (M + H)+: 397.06229, found: 397.06122.White solid , mp: 218–220 °C; 4.1.2.5.1H NMR  δ: 1.79 , 4.71 , 7.25 , 7.31 , 7.52–7.56 , 7.83 ; 13C{1H} NMR  δ: 12.6 (CH3), 36.1 (CH), 57.6 (C-5), 98.4(C-3a), 119.8 (CN), 120.2 (Ar-C), 121.4 (Ar-C), 129.2 (Ar-C), 130.1 (Ar-C), 130.3 (Ar-C), 131.5 (Ar-C), 136.3 (Ar-C), 143.0 (Ar-C), 144.0 (C-3), 145.7 (C-7a), 159.4(C-6); HRMS (ESI-TOF) m/z calcd. for C20H14BrClN4O (M + H)+: 441.01178, found: 441.01042.White solid , mp: 224–226 °C; 4.1.2.6.1H NMR  δ: 1.78 , 4.72 , 7.17 , 7.28  7.30–7.33 , 7.54 , 7.83 ; 13C{1H} NMR  δ: 12.6 (CH3), 35.9 (CH), 58.0 (C-5), 98.7(C-3a), 115.3 ,119.9 (CN), 121.4 (Ar-C), 129.2 (Ar-C), 129.7 , 130.2 (Ar-C), 136.4 (Ar-C), 139.7 , 144.0 (C-3), 145.7(C-7a), 159.3(C-6), 161.2 ; HRMS (ESI-TOF) m/z calcd. for C20H14ClFN4O (M + H)+: 381.09184, found: 381.09077.White solid , mp: 192–194 °C; 4.1.2.7.1H NMR  δ: 1.79 , 4.56 , 6.72 , 7.04 , 7.18 , 7.53 , 7.82 , 9.36 ; 13C{1H} NMR  δ: 12.6 (CH3), 36.0 (CH), 58.8 (C-5), 99.3(C-3a), 115.2 (Ar-C), 120.0 (CN), 121.3 (Ar-C), 128.8 (Ar-C), 129.2 (Ar-C), 130.1 (Ar-C), 133.8 (Ar-C), 136.4 (Ar-C), 143.8 (C-3), 145.8(C-7a), 156.3 (Ar-C), 159.1(C-6); HRMS (ESI-TOF) m/z calcd. for C20H15ClN4O2 (M + H)+: 379.09618, found: 379.09505.White solid (0.310 g. 82%), mp: 212–214 °C; 4.1.2.8.1H NMR  δ: 1.78 , 3.75 , 4.63 , 6.90 , 7.17 , 7.21 , 7.53 , 7.83 ; 13C{1H} NMR  δ: 12.6 (CH3), 35.9 (CH), 55.0(OCH3), 58.5 (C-5), 99.1(C-3a), 113.8 (Ar-C), 120.0(CN), 121.3 (Ar-C), 128.9 (Ar-C), 129.2 (Ar-C), 130.1 (Ar-C), 135.5 (Ar-C), 136.4 (Ar-C), 143.9 (C-3), 145.8(C-7a), 158.2 (Ar-C), 159.2(C-6); HRMS (ESI-TOF) m/z calcd. for C21H17ClN4O2 (M + H)+: 393.111829, found: 393.11077.White solid , mp: 218–220 °C; 4.1.2.9.1H NMR  δ: 1.32 , 1.78 , 4.00 , 4.62 , 6.88 , 7.15 , 7.21 , 7.53 , 7.83 ; 13C{1H} NMR  δ: 12.6 (CH3), 14.7 (CH3), 35.9 (CH), 58.6 (C-5), 62.9(OCH2), 99.1(C-3a), 114.3 (Ar-C), 120.0(CN), 121.3 (Ar-C), 128.8 (Ar-C), 129.2 (Ar-C), 130.1 (Ar-C), 135.4 (Ar-C), 136.4 (Ar-C), 143.9 (C-3), 145.8(C-7a), 157.5 (Ar-C), 159.2(C-6); HRMS (ESI-TOF) m/z calcd. for C22H19ClN4O2 (M + H)+: 407.12748, found: 407.12642.White solid , mp: 190–192 °C; 4.1.2.10.1H NMR  δ: 1.84 , 4.75 , 7.29 , 7.35–7.38 , 7.47 , 7.55 , 7.69 , 7.85 ; 13C{1H} NMR  δ: 12.6 (CH3), 36.3 (CH), 58.0 (C-5), 98.8 (C-3a), 120.0(CN), 121.4 (Ar-C), 126.6 (Ar-C), 126.9 (Ar-C), 127.4 (Ar-C), 128.4 (Ar-C), 128.9 (Ar-C), 129.2 (Ar-C), 130.2 (Ar-C), 136.4 (Ar-C), 138.9 (Ar-C), 139.7 (Ar-C), 142.7 (Ar-C), 144.0 (C-3), 145.8 (C-7a), 159.4 (C-6); HRMS (ESI-TOF) m/z calcd. for C26H19ClN4O (M + H)+: 439.13256, found: 439.13138.White solid , mp: 204–206 °C; 4.2.4.2.1.http://www.kinase-screen.mrc.ac.uk/). 4j biochemical kinase inhibitory property was determined against a panel of 139 protein kinases as described previously  (50–1000 cpm/pmole) and incubated for 30 min at room temperature. Assays were stopped by adding 5 µL of 0.5 M (3%) orthophosphoric acid and then harvested onto P81 Unifilter plates with a wash buffer of 50 mM orthophosphoric acid. IC50 curves were developed as % of DMSO control, and IC50 values were calculated using GraphPad Prism software.ICeviously . PKBβ or4.2.3.4.2.3.1.p-values of correlation. For example, a value of −2, , for AKT2 indicates that when AKT2 expression is high, patient outcome is better with longer survival, whereas a positive 2 value , indicates the opposite: high expression of AKT2 predicts worse outcome or poorer survival.The AKT2 expression correlation with overall survival for tumour indication is based upon data generated through the Lumin Bioinformatics Software of Champions Oncology, Inc. This signature reflects the correlation of AKT2 mRNA expression with the overall survival in each of the TCGA cancer indications described. The individual values are sign-corrected log10 4.2.3.2.https://singlecell.broadinstitute.org/single_cell). We explored the “Single-cell RNA-seq of adult and paediatric glioblastoma” dataset consisting of 24,131 single-cell sequences from patients with IDH1 wild-type glioblastoma [To understand expression across various cell states of glioblastoma, we queried AKT2 levels in two previously published single-cell RNA sequencing datasets available on the Single Cell portal of Broad Institute, MIT and Harvard, USA , RAW264.7, HEK293T, and BV2  cells were cultured in Dulbecco’s Modified Eagle Media  supplemented with 10% FBS and 1% penicillin and streptomycin. GBM6 and GBM22 cells were cultured in DMEM supplemented with 10% FBS, 1% penicillin and streptomycin, 10 μg/mL insulin, and 20 ng/mL hEGF. GBM12 and GBM76 cells were cultured in neurosphere media consisting of KnockOut DMEM/F-12 Basal Media supplemented with StemPro NSC SFM Supplement, 10 µg FGF, 10 µg EGF, L-glutamine (Corning #25005CI) 10 mL of 200 mM solution, and 1% penicillin and streptomycin. GBM6, GBM12, GBM22, and GBM76 cells were acquired from the Brain Tumour PDX National Resource, Mayo Clinic, USA. Resected tumours from patients were propagated subcutaneously in immunocompromised mice and the tumours were dissociated and cultured in either growth media with FBS or neurosphere media in stem conditions. Immunophenotyping has not been carried out on these tumours. All primary GBM cells were established by the Mayo Clinic .Mammalian cells were all grown in a humidified incubator with 5% CO4.3.2.Cell viability assays were carried out as stated previously . To meas4.3.3.4j or 1 μM MK-2206 (Selleckchem #S1078) for 21 days in triplicates. After 21 days, representative images were taken of each well using the Zeiss Axiovert Live microscope. Diameters of the neurospheres were quantified using ImageJ software, and graphs were plotted on GraphPad Prism.A neurosphere formation assay is a cellular event wherein the 2D primary glioma cells aggregate to form a 3D organoid structure  when cultured in stem cell media. GBM12 and GBM76 cells were plated at 4000 cells per well in neurosphere media supplemented with either DMSO, 20 μM 4.4.p-value has been detailed in figure legends. All experiments were repeated 2–3 times with multiple technical replicates to be eligible for the indicated statistical analyses, and representative images were shown. All results are presented as mean ± SD unless otherwise mentioned. Data were analysed using GraphPad Prism statistical package unless otherwise mentioned. TCGA data mining and corresponding statistical analyses were performed by Lumin Bioinformatics webtool, as stated previously.Details of all statistical tests and multiple comparisons used to derive Click here for additional data file.


The arterial anatomy of the face is extremely variable. Despite numerous cadaver dissections and anatomical descriptions, the exact location of the superficial facial arteries remains unpredictable. This ignorance is a determining factor in the pathophysiology of intravascular filler injections, potentially causing skin necrosis and blindness.The main objective of this study is to evaluate the accuracy of an augmented reality (AR) application that visualizes the individual arterial anatomy of the face.A workflow was developed during which a magnetic resonance angiography (MRA) mapped the superficial arteries of the face. The images were further processed into an AR image that was visualized on the patient’s face using a specifically designed smartphone application. The accuracy of the AR image and the position of each individual artery were analyzed using duplex ultrasound (US).A total of 216 facial arteries were visualized in 20 patients. The superficial temporal (100%), supratrochlear (92.5%), facial (75%), and angular (82.5%) arteries were visualized the most. The inferior labial (17.5%), dorsal nasal (22.5%), and supraorbital (42.5%) arteries were the most difficult to visualize through MRA. The average deviation between the artery visible on the AR image and the location assessed by US was 0.30 mm (standard deviation = +/− 0.66 mm). There were no complications reported.The combination of a risk-free MRA to map the individual arteries of the face and the processing into an AR image may be considered as a useful and accurate tool during dermal filler injections to potentially minimize the risk of intravascular filler injections. The increase of augmented reality (AR) is one of the biggest breakthroughs of the 21st century. The use of AR in the modern society can be appreciated through multiple applications in the commercial world, the gaming industry, the architectural business, and then some.1 In the same year, 1995, the first clinical case was described in which AR technology was used to accurately position dental implants.2It did not take too long before AR made its introduction into the medical world, with the first reports of AR in surgery dating back 25 years ago.The core idea of AR—enhancing objects of the real world by computer-generated information—can truly be appreciated when looking at the patient’s own anatomy through AR. And for that, surgery is probably one of the most exciting playgrounds within that field. Allowing the surgeon to basically “see through the patient’s skin” is a real asset in surgical planning and execution. Although plastic surgeons are well trained in human anatomy, they are often confronted—and even more so fascinated—by the numerous anatomical variations that exist within the human body. For that reason, we perform preoperative imaging to visualize in detail the individual anatomy, the location of the perforators (in case of flap surgery), and the relationship between different tissues. The concept of anatomical variation—a term that generates more than 24,000 results on PubMed—is what makes surgery not only exciting/fascinating but also dangerous, and sometimes even frightening. The uncertainty of the exact anatomical location of a certain structure is one of the only certainties there is when stepping into the operating field. When dealing with anatomical variations, open surgery has a clear advantage over closed procedures as it allows the surgeon to analyze and meticulously dissect the tissues. However, when performing minimally or noninvasive operations, there is no clear view of the individual anatomy, and one must trust their theoretical (book) knowledge and the experience built up throughout the years.3-7 The pathway of intra-arterial hyaluronic acid (HA) injections has been described numerously.9 Unfortunately, possible solutions or surgical guidance tools to showcase each patient’s arterial network are still lacking.With regard to dermal filler injections, knowledge of the arterial anatomy is of crucial importance, and the lack of these insights may lead to devastating complications such as skin necrosis and blindness.11 The obtained images provided the necessary information to develop an AR image that was visualized on the patient’s face. The projection of this arterial network was eventually checked by duplex ultrasound (US) in order to evaluate its accuracy with regard to the assumed location of each individual artery of the face. This workflow may potentially be the first breakthrough of the use of AR in the field of aesthetic and noninvasive surgery.This study may provide a possible workaround to deal with the uncertainty of the anatomical variation when performing filler injections. A previously described magnetic resonance angiography (MRA) imaging technique was used to map the superficial arterial network of the face .The clinical study was approved by the ethical board of the hospital  with reference number 2020/14. The study was fully conducted at the hospital of AZ Zeno in Knokke (Belgium) and according to the principles of the declaration of Helsinki.11 All images were acquired on a 3-Tesla (3-T) full-body magnetic resonance (MR) system, using a dedicated 21-channel head coil. As described previously, each patient was first positioned in the front of an infrared lamp to heat up the face before the MRA.10-12Only patients aged between 18 and 65 years were included in the study. Written consent was provided, by which the patients agreed to the use and analysis of their data. Scans were performed between March and May 2021. Exclusion criteria were non-MRI-compatible internal devices (such as a pacemaker), metal plates in the face or skull, dental braces , tattoos on the face (but not permanent make-up), claustrophobia, vascular disease, and congenital or acquired facial anomaly. All included patients underwent a 3-dimensional (3D) Time of Flight Multiple Overlapping Thin Slab Acquisition (3D TOF MOTSA) MRA, of which the exact sequence has been published before.13 Segmentation was performed by thresholding the vessel enhanced image. The 3D mesh was computed using the marching cubes method. The end results were exported into Standard Triangle Language (STL) volumes, which were then compared with the native DICOM images and rendered maximum intensity projection volume to evaluate which arteries were visualized by the MRA and further segmented into the 3D STL volume. A total of 18 arteries were taken into account, from both the left and right sides of the face: facial (Fa), superior (SL) and inferior labial (IL), angular (Ang), lateral nasal (LN), dorsal nasal (DN), superficial temporal (ST), supratrochlear (STr), and supraorbital (SO) arteries.The native Digital Imaging and Communications in Medicine (DICOM) images of each patient were further processed to segment the arteries of the face. By using a segmentation and separation technique, a 3D volume of the superficial, subcutaneous  arterial network was obtained. The dedicated algorithm was developed by Augmented Anatomy BV  using open-source libraries for medical imaging processing . A multiscale Jerman vessel enhancement function was applied on the MOTSA images to highlight arteries.To process the arterial network into an AR image, dedicated facial recognition software was used. The facial contour of each patient was scanned, and 68 unique reference points were determined. These were further matched according to the 3D volume of the arterial network. The reference points followed the contours of the jawline, chin, mouth, nose, eyes, and eyebrows. A smartphone application  was used to visualize the AR image on each patient’s face. Using the smartphone’s back camera, the patient’s face was scanned and analyzed by the facial recognition software. The tracked reference points were then matched to the processed 3D arterial volume to accurately display the unique set of facial arteries on the patient’s face through AR. To analyze how accurate the arteries were positioned on the AR image, duplex US was used. The visualized arterial network was drawn on each patient’s face, using the AR projection as a guide . The exaBetween March and May 2021, a total of 20 volunteers  were recruited to map their individual arterial network of the face. Of the 20 patients, there were 4 males and 16 females. Dental braces or metal wires were present in 7 patients, resulting in metal artifacts for the superior and inferior labial arteries in 7 cases.Each scan was processed into a 3D volume that was projected onto the patient’s face, using Artery 3D. Results were generated instantly, thanks to the automation of the segmentation and separation algorithm. 14 Within the field of plastic and reconstructive surgery, the use of AR has been described for a number of procedures but has yet to find a solid base to be implemented in the plastic surgeon’s daily practice. Some authors have described its use in the visualization of the arterial anatomy during preoperative flap planning, while others found a benefit in AR-guided flap volume visualization.15-18 One of the most interesting applications was described by Pratt et al in 2018, in which the Microsoft HoloLens  was used to visualize perforating vessels of the lower limb through AR.19 The AR visualization was generated from the patient’s own computed tomography angiography (CTA) images and allowed the surgeon to accurately locate the perforating vessels of the vascular trunk of the lower limb. A more “sophisticated” implementation of an intraoperative AR system has been published 2 years later by Katayama et al.20 One of the most popular free flaps in reconstructive surgery is the deep inferior epigastric artery perforator (DIEAP) flap. Aiding the surgeon by means of an AR-based system to accurately locate the perforator vessels and their intramuscular course may result in better operation planning, faster flap dissection times, and less donor site morbidity, eventually leading to better postoperative outcomes.21 Even though not fully embraced yet, these early reports are a perfect example of why our discipline would profit from a kind of technology that lets you “see through the patient’s skin” using the newest and state-of-the-art 3D and AR visualization systems.Neurosurgery is probably the number one player in the field of AR-guided surgery and has truly embraced the use of this exciting new technology in its day-to-day surgical planning.22–25Demanding any kind of invasive or potential harmful investigation like a CTA or classic angiography in aesthetic cases would be unethical and completely unjustifiable. However, taking into account the ever-increasing reports on anatomical variation, as well as those portraying vascular-related complications of dermal filler products, there is a need to help the injector to locate potential facial danger zones.24 Related to vascular occlusions, the recommendations entail a thorough knowledge of the vascular anatomy, adequate training, and appropriate injection technique. Knowledge of the vascular anatomy is a necessity. However, the numerous described variations of almost every relevant superficial artery of the face will undoubtedly cause some level of uncertainty for even the highest trained injectors.25 Regarding appropriate techniques, it is recommended to aspirate before injecting any amount of HA and to use blunt microcannulas to minimize the risk of vessel wall perforation.24 However, even those 2 widely proclaimed “safety measures” do not seem waterproof and cannot ensure enough safety during filler injections. Van Loghem et al. published a detailed report in 2018, showing that aspiration tests are heavily influenced by several variables, such as needle diameter, needle length, and rheological properties of soft tissue fillers (STF).26 The longer and narrower the needle of the filler syringe, the more false-negative  results were observed, due to a higher flow resistance during aspiration. The same accounts for the rheological properties of the used STF, where high cohesive products will often give negative aspiration test results. Only one-third (112/340) of the aspiration tests were positive within 1 second of aspiration, whereas 37.6% of the tests still were false-negative after 10 seconds of aspiration. Finally, 30% of the tests were positive when aspirating between 1 and 10 seconds. In conclusion, aspirating for at least 10 seconds seems mandatory, but even then, only 63% (213/340) of the tests were true-positive. Reports focusing on cannula size also claim that cannulas smaller than 25 gauge behave like needles within the human body and can easily puncture a vascular wall when enough force is applied.28In 2016, the Global Aesthetic Consensus Group published a list of recommendations to potentially prevent and manage complications related to HA injections.24 The cornerstone remains abundant use of hyaluronidase to dissolve the HA when the injector fears eminent skin necrosis or retinal infarction. However, although highly recommended and lifesaving in several case reports, its success remains doubtful in the case of retinal artery occlusion.29Multiple algorithms have been published to treat the patient in case of an STF-induced vascular occlusion.12Without a doubt, the best way to treat complications is by preventing them. In the case of STF-induced vascular occlusion, an accurate visualization of the individual arterial anatomy may be useful, as it eliminates the uncertainties when trusting solely the standard anatomical knowledge. In our opinion, the previously described MRA sequence is the only published imaging method to date that provides an all-in-one overview of the relevant arterial anatomy for any injector.10 However, it is interesting to notice that the developed MRA sequence results in a much more complete visualization of the facial arterial network, when performed on a 3-T MRI. Compared with our first study (which was performed on a 1.5-T MRI), we have an overall far better visualization of the facial arteries, and more in particular of the Fa (75.0%), Ang (82.5%), ST (100.0%), and Str (92.5%) arteries.10 As these arteries are located in the riskiest zones with regard to vascular filler complications , the importance of their visualization—and more importantly, their anatomical variation—cannot be underestimated. If one would exclude the patients who wore dental braces (7 of the 20) for the statistical analysis of the labial arteries, the sensitivity of the MRA sequence would increase from 17.5% and 45.0% to 26.9% and 69.2% for the IL and SL, respectively. Moreover, with a mean average deviation of less than 1 mm between the AR location and US location—as proven by this study—we are quite confident about the clinical importance of the developed AR application.The sensitivity of this MRA sequence was already evaluated in a previous study and is beyond the scope of this article.31 However, the added technical complexity of visualizing small vascular structures as a non-radiologist, the dexterity that is needed to hold the probe in one hand and inject an STF with the other, and the issues of sterility when guiding the needle through the conductive gel do seem severe limitations in the practical implementation of this guidance system.The major downside of MRA remains the metal artifacts, which are known to disturb the image. As the population that wears or wore braces, often followed by dental wires, is quite abundant, we do realize that the visualization of the labial arteries will be very variable and dependent of the examined patient population. Despite these shortcomings, an MRI-based workflow remains the only imaging technique that provides a risk-free and noninvasive 3D overview of the facial vasculature. US-based systems have been shown to provide some level of guidance during STF injections.We do realize that there is a margin of error in the presented workflow. Both the process of drawing the arteries on the face and determining the US-guided location of each artery may result in a deviation between the assumed and real arterial location. Additionally, the used marker to draw the arteries has a thickness of 1 mm, which may influence the measurements as well. Deviations for each individual artery ranged between 0 and 3 mm, with only the ST artery deviating twice 4 mm (in patients 9 and 15) and once 5 mm (patient 1).However, by including well over 200 individual arteries, we assume that the calculated average deviations provide a quite trustful picture of the levels of accuracy of the developed application. Moreover, we especially chose to use the duplex US to eliminate possible arterial signals of a small, more superficial arterial branch that may be confounded with the relevant and targeted artery.The current version of the AR visualization method does not take depth into account. It is true that the arteries run at different levels within the subcutaneous tissue and that depth information is crucial when injecting filler products. Showing the depth of each artery  may certainly bring added value to this workflow and will hopefully be part of future software updates. In addition, the use of AR glasses will further improve the accurate tracking of the facial contours, hence further increasing the accuracy of the AR visualization of the facial arteries.The world of STF injections is a massively booming business. The number of injectors increases day by day and so does the number of complications. Although measurements such as knowledge of the anatomy, correct injection techniques, and point-by-point treatment algorithms may provide some level of security, it is only by knowing the exact location of the facial arteries that filler-induced vascular occlusions may truly be avoided. This study proves that not only the developed MRA sequence is able to map out the most relevant superficial arteries of the face and help the injector in analyzing the facial danger zones, but also the developed AR application can additionally provide an accurate (up to 0.1 mm) and real-time visualization of the individual anatomical variations of each patient. In these exciting times of technological innovation, evolutions in the field of augmented and virtual reality may hopefully become a part of the injector’s armamentarium in the near future. After all, it is the patient’s safety that remains the cornerstone of any medical or surgical treatment, and we should embrace any innovation or development that strives toward that uniform goal.


Radiation therapy (RT) and hormone receptor (HR) inhibition are used for the treatment of HR-positive breast cancers; however, little is known about the interaction of the androgen receptor (AR) and estrogen receptor (ER) in response to RT in AR-positive, ER-positive (AR+/ER+) breast cancers. Here we assessed radiosensitisation of AR+/ER+ cell lines using pharmacologic or genetic inhibition/degradation of AR and/or ER.AR.Radiosensitisation was assessed with AR antagonists , ER antagonists  or using knockout of AR knockout compared to Cas9 cells (rER: 1.07 ± 0.11), and no additional radiosensitisation was achieved with tamoxifen or fulvestrant compared to Cas9 cells (rER: 0.84–1.19).Treatment with AR antagonists or ER antagonists in combination with RT did not result in radiosensitisation changes (radiation enhancement ratios [rER]: 0.76–1.21). Fulvestrant treatment provided significant radiosensitisation of CAMA-1 and BT-474 cells (rER: 1.06–2.0) but not ZR-75-1 cells (rER: 0.9–1.11). Combining tamoxifen with enzalutamide did not alter radiosensitivity using a 1 h or 1-week pretreatment (rER: 0.95–1.14). Radiosensitivity was unchanged in While radiosensitising in AR + TNBC, AR inhibition does not modulate radiation sensitivity in AR+/ER+ breast cancer. The efficacy of ER antagonists in combination with RT may also be dependent on AR expression.  Breast cancer is a heterogeneous disease, classified largely by the expression of the estrogen receptor (ER), progesterone receptor (PR), and by amplification of the human epidermal growth factor receptor 2 (HER2) . Over 80Further, the roles of both AR and ER in the radiation response are not well understood. Previous studies indicate that TNBC patients with low AR expression have decreased rates of local recurrence following radiation therapy (RT) and that AR protein expression is a biomarker of response in AR+ TNBC models . AdditioAndrogen receptor expression has also been investigated as a contributor to the radiation response in multiple types of cancer, including prostate cancer, breast cancer and glioblastoma –12. AR hAR using CRISPR-Cas9, does not radiosensitise AR+/ER+ breast cancer cells in vitro. Additionally, dual inhibition or degradation of AR and ER is not sufficient, in most models, to radiosensitise AR+/ER+ breast cancer cells in vitro suggesting that these receptors may not be compensating for each other when co-expressed. Further, combination treatment of AR inhibition or knockout with ER inhibition or degradation does not have a synergistic effect on radiosensitisation, suggesting that AR and ER are not directly and exclusively compensating for their role in the radiation response. While our previous data suggest that inhibition or degradation of ER results in radiosensitisation [Having previously demonstrated that ER inhibition is an effective radiosensitisation strategy in ER+, AR-low breast cancers  and AR itisation , here we2 incubator. MCF-7 cells were grown in DMEM media (ThermoFisher 11965092) containing 1% penicillin/streptomycin (ThermoFisher 15070063) and 10% fetal bovine serum . BT-474 and ZR-75-1 cells were grown in RPMI 1640 media (ThermoFisher 11875093) containing 1% penicillin/streptomycin and 10% FBS. CAMA-1 cells were grown in EMEM media (ThermoFisher 15070063) containing 1% penicillin/streptomycin and 10% FBS. ACC-422 cells were grown in MEM media (ThermoFisher 11095080) containing 1X Insulin-Transferrin-Selenium-Ethanolamine , 1% penicillin/streptomycin and 15% FBS. Where noted, charcoal stripped serum  was used in place of FBS to remove hormones and growth factors. When CSS was used, the base media was also free of phenol-red. DNA fingerprinting was performed using short tandem repeat (STR) profiling at the University of Michigan Advanced Genomics Core. The MycoAlert Mycoplasma Detection kit (Lonza LT07) was used to test cells routinely for mycoplasma.All cells were grown at 37 °C in a 5% COAAVS1 (5’ CACCGGGGGCCACTAGGGACAGGAT 3’).CRISPR cell lines were generated using the lentiCRISPRv2 plasmid (Addgene #98291) and the AR guide sequence (5’ CACCTCCAGCTTGATGCGAGCGTG 3’). As previously described , the lenn = 3).Cells were plated in a 96-well plate and allowed to fix overnight. Cells were treated with media containing 1.0 nM–10 μM ARD-61. After growing for 72 h cell viability was assessed with AlamarBlue (ThermoFisher DAL1100) at a concentration of 10% of the well volume. Viability was calculated using a plate reader by measuring the absorbance of each well with an excitation wavelength of 540 nm and an emission wavelength of 590 nm. GraphPad Prism 8.0 was used to calculate a dose-response curve and half-maximal inhibitor concentration (IC50). Six technical replicates were used for each experiment, and the experiment was repeated three times (n = 3).Cells were plated and allowed to fix overnight. Pretreatment (1–24 h) with drug-containing media was followed by radiation (0–6 Gy). After growth for 1–4 weeks, colonies were fixed with methanol/acetic acid and stained with crystal violet. Colonies with >50 cells were counted, and data were analysed using the linear-quadratic model. All combination groups were normalised to the drug-only control (treated with 0 Gy RT). GraphPad Prism 8.0 was used to visualise the data. All experiments used three technical replicates and were repeated in triplicate (Cells were harvested at indicated time points. RIPA buffer (Thermo Fisher 89901) containing protease and phosphatase inhibitors  was used to lyse cells. For nuclear fractionation experiments, the NE-PER Nuclear and Cytoplasmic Extraction Reagents (Thermo Scientific 78835) were used to separate the nuclear and cytoplasmic cellular fractions. All samples were sonicated and then standardised using a BCA assay. Samples were run in a 4–12% NUPAGE Bis-Tris protein gel at 120 V then transferred to a PVDF membrane, blocked in 5% milk in TBST, and primary antibody  was added overnight. Anti-rabbit secondary antibody  was then added and blots were visualised using ECL Prime on a ChemiDoc Imaging System. ImageJ was used for the quantification of western blots.AQP3 , SEC14L2 , PGR , AR , GREB1 , and GAPDH  were obtained from Integrated DNA Technologies. The ΔΔCt comparison was calculated by comparing the genes of interest with GAPDH as an internal control, then comparing each condition to cells cultured in FBS as a control. The relative expression of each gene was then assessed. All experiments used three technical replicates, and data are represented as relative expression ± SEM from three independent experiments (n = 3).To assess changes in mRNA levels, cells were first plated in complete media containing FBS. The next day, cells were pretreated with media without phenol-red, containing CSS for 48 h. Stimulation was then performed with β-estradiol or metribolone (R1881). After 24 h of stimulation, RNA was extracted with TRIzol using the miRNeasy kit for RNA isolation (Qiagen 217004). Reverse transcription was performed using random primers (Thermo Fisher 48190011), dNTPs (Thermo Fisher 18427013) and the Superscript III enzyme (ThermoFisher 18080085). cDNA was then diluted 1:5 after completion of reverse transcription. Fast SYBR Green Master Mix (Thermo Fisher 4385612) reagents were used to perform a ΔΔCt comparison of expression of gene-specific primers following hormone stripping with CSS, stimulation with E2, or stimulation with R1881 using the QuantStudio 6 Flex Real Time qPCR System. Primers for Enzalutamide , apalutamide , darolutamide , tamoxifen (HY-13757A), fulvestrant (HY-13636) and β-estradiol  were obtained from MedChemExpress. Seviteronel (VT-464) was obtained from Innocrin Pharmaceuticals. ARD-61 was provided by the labs of Shaomeng Wang and Arul Chinnaiyan at the University of Michigan. R1881 was provided by the lab of Arul Chinnaiyan at the University of Michigan.A Kimtron IC-225 orthovoltage machine was used to provide X-ray radiation at the University of Michigan Experimental Irradiation Core. In keeping with previous work, a dose rate of 2 Gy/min was used –31.t-test was used to compare treatment groups. All data meet the assumptions for the statistical tests that were used, and the variance between comparison groups is similar.GraphPad Prism 8.0 was used to perform all statistical analyses. For the determination of IC50s, a dose-response curve was calculated. For all in vitro experiments, a one-way ANOVA with Dunnett’s multiple comparisons or a one-way Student’s First, functional AR and ER activity was validated by western blot and through qPCR experiments in AR+/ER+ breast cancer cell lines  and AR  target genes in CAMA-1, ZR-75-1 and BT-474 cells after stimulation of β-estradiol or R1881. First, AR transcript levels were assessed following CSS conditions or under stimulated conditions. While growth in CSS media was sufficient to induce an increase in levels of AR transcripts, stimulation with β-estradiol or R1881 resulted in a decrease in relative expression in CAMA-1 and BT-474 cells  in CAMA-1, BT-474 and ZR-75-1 cells  at 6 and 24 h prior to RT, in contrast to the 1 h pretreatment used in Fig. Next to further assess radiosensitivity using additional pharmacologic AR inhibitors, clonogenic survival assays were performed with apalutamide, darolutamide or seviteronel. While apalutamide and darolutamide are both second-generation AR antagonists, apalutamide is structurally similar to enzalutamide. In contrast, darolutamide is structurally unique compared to enzalutamide and apalutamide and has less blood-brain barrier penetration, offering a unique clinical application as serum testosterone levels are not altered in CRPC patients with darolutamide treatment , 37. SevAs a control, clonogenic survival assays were also performed in AR−/ER+ MCF-7 cells, where treatment with 0.5–2.0 µM apalutamide , tamoxifen, or the selective estrogen receptor degrader (SERD), fulvestrant. While previous work has demonstrated a role for tamoxifen or fulvestrant in the radiosensitisation of ER+ breast cancer models in vitro and in vivo , the rolWe next wanted to understand whether AR and ER may have an overlapping function allowing the hormone receptors to compensate in response to radiation treatment. To investigate this, clonogenic survival assays were performed in CAMA-1, ZR-75-1 and BT-474 cells pretreated for 1 h with 2.0 µM tamoxifen and/or 2.0 µM enzalutamide prior to RT. There was no significant change in radiosensitisation in cells treated with tamoxifen alone (rER: 0.90–1.21), enzalutamide alone (rER: 0.89–1.00) or the combination of tamoxifen and enzalutamide  or Cas9 control cells containing the Cas9 protein and a control guide (AAVS1) were generated in CAMA-1 or ZR-75-1  models and other AR+ cancers . In AR+/Further, our data indicate that anti-androgen or anti-estrogen therapies may be effective radiosensitisation strategies in some, but not all AR+/ER+ breast tumours, suggesting a need for additional biomarkers of response for AR and/or ER antagonists. While an AR:ER positivity ratio of 78% has been demonstrated to have the prognostic capacity in AR+/ER+ tumours , a more Despite these findings, there are also a few limitations to the current study that are worth noting. These studies use tamoxifen instead of 4-hydroxytamoxifen (4-OHT), which is an active metabolite of tamoxifen, and 100× more potent than tamoxifen . As tamoWhile AR-targeting therapies have become a mainstay in the treatment of prostate cancers, ongoing preclinical and clinical studies in AR+ tumours have demonstrated therapeutic potential for the treatment of AR+ breast cancers using AR antagonists. In a phase II trial (NCT01889238), enzalutamide has been shown to provide clinical benefit to ~30% of AR+ TNBC patients . AdditioSupplementary Figures and CaptionsAJ Checklist


Prostate cancer (PCa) is a major type of cancer in man worldwide. Androgen deprivation therapy (ADT) and the next‐generation androgen receptor (AR) pathway inhibitors have acquired great success in treating PCa. However, patients treated with ADT or AR targeted therapy are inevitably developing into castration‐resistant prostate cancer (CRPC) or becoming drug resistance. The role of mRNA 5‐methylcytosine (m5C) modification in cancers is largely unknown. This study aimed to explore the role of the m5C methyltransferase NSUN2 in Prostatecancer (PCa).5C sites.The expression of NSUN2 and its clinicopathological impact were evaluated in PCa cohorts. The effect of NSUN2 on the biological characteristics of PCa cells was investigated on the basis of gain‐offunction and loss‐of‐function analyses. Subcutaneous models further uncovered the role of NSUN2 in tumor growth. Epi‐transcriptome assays with RNA bisulfite sequencing (RNA‐BisSeq) analysis and in vitro enzyme reaction assays were performed to validate the targeted effect of NSUN2 on AR. AR‐binding sites in the NSUN2 promoter were investigated by ChIP and luciferase assays to uncover the interplay between NSUN2 and AR signaling. RIP‐qPCR and EMSA methods were performed to confirm that YBX1 binds to AR m5C modification in a m5CYBX1‐dependent manner. Strikingly, treatment with enzalutamide, an effective AR inhibitor, reduces NSUN2 expression and decreases the m5C modification level in prostate cancer cells. Finally, we found that AR transcriptionally regulates NSUN2.NSUN2 is highly expressed in PCa and predicts poor outcome. NSUN2 plays roles as a PCa oncogene both in vitro and in vivo. Depletion of NSUN2 results in decreased expression and activities of AR, including AR‐V7. Mechanistically, NSUN2 posttranscriptionally stabilized AR by cluster mNSUN2 stabilizes AR mRNA through cluster 5‐methylcytosine modification and activates a positive feedback loop to promote prostate cancer. NSUN2 expression is upregulated in PCa and associated with a worse prognosis.AR mRNA is modified by NSUN2 and is stabilized in an m5C‐YBX1‐dependent manner.The m5C modification located in the 5′ region of AR mRNA, influenced several AR variants including AR‐V7.NSUN2 expression is also transcriptionally regulated by AR and can respond to ADT and ARSI treatment. It occurs primarily through AR signalling reactivation in a ligand‐dependent or ligand‐independent manner.5C) modifications were first discovered in abundant and stable tRNAs and rRNAs.5C modification has been identified to regulate mRNA metabolism and translocation.5C modification could impact various biological events, such as embryonic development, myelopoiesis5C methyltransferases (‘writers’) of mRNA to date.5C 'readers.'Kip2 in an m5C‐dependent manner.RNA 5‐Methylcytosine  was purchased from Selleck, Shanghai.2.2C4‐2, LNCaP, 22RV1 were maintained in RPMI 1640 basic medium  with 10% FBS .NSUN2 siRNAs were synthesized by Biosun Company.Lipofectamine 3000 (Invitrogen) was used for plasmid and siRNA transfection following the manufacturer's protocols.2.35C and cytosine was calibrated by the standard curve generated by the standards (purchased from APExBIO). Following the standard protocol, add 200‐300 ng of mRNA to 25 µl of dilution buffer, digest with nuclease P1 (1 U) for 2 h at 42°C, followed by alkaline phosphatase (1 U) and NH4HCO3  treated at 37°C incubate for 2 h, and finally filter through a filter for mass spectrometry analysis.mRNA from C4‐2 cells was purified using the Dynabeads™ mRNA Purification Kit. The purified mRNA is digested into single nucleotides and quantitatively detected by LC/MS/MS by Shanghai Biotree Co., Ltd. The content of m2.45C antibody  at 4°C. Then incubated with secondary antibody  for 1 h and exposed with LAS 4000 mini for 30 seconds.Samples were spotted onto Amersham HybondTM‐N+ membranes  and cross‐linked with UV, then washed with wash buffer for 7 min and blocked for 1 h at room temperature, with anti‐m2.5Cells were fixed with methanol for 15 min and then permeabilized with 0.1% Triton X‐100 on ice for 15 min. This was followed by blocking with 10% FBS for 1 h, followed by incubation with primary antibody overnight at 4°C, followed by incubation with secondary antibody for 1 h, and finally mounting with DAPI‐containing mounting medium . The fluorescence intensity was quantified by ImageJ.2.6Cells were pre‐treated for 72 h. Then, add 50 µl of supernatant to the chip   and wait for 5 min. Finally, the chip was put into the detection instrument .2.7The sequence probes were designed in our laboratory. These probes were synthesized by a standard RNA synthesis kit  following the manufacturer's protocols.2.8Cell lysates were prepared with RIPA cell lysis buffer. Briefly, mix 50 µl streptavidin magnetic beads with 50 pmol 3′‐biotin‐labelled RNA probes and incubated for 30 min with agitation. After incubation, add 100 mg protein lysate and incubated for 60 min at 4°C with agitation. The probe sequences were as follows:probe‐mut: AugAugAugAagaagAagAagAagAagaagaagaagaagaagaagaagaagaagaagaagaagaagaagaagprobe‐normal: CugCugCugCagcagCagCagCagCagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcag2.92, 80 mM KCl, 0.2 U µl−1 RNasin, 0.2 U µl−1 DNasin, 4% glycerol, 10 mM DTT and 15 mM HEPES (pH 7.9) incubated at 16°C overnight.0.15 nmol probe and 0.15 nmol NSUN2 protein were added into a buffer contain 0.8 mM SAM, 1.5 mM MgCl2.10Purified mRNA (500 ng) was converted with the EZ RNA Methylation Kit (Zymo Research).2.112.11.1We collected samples from Fudan University Shanghai Cancer Center (FUSCC). The tissues were put into a homogenization tube, grinding beads and 1 ml of TRIzol (Invitrogen) were added. After grinding, it was centrifuged at 12 000 rpm/min for 15 min, and the supernatant was collected. RNA was purified by TRIzol (Invitrogen). All RNA libraries were constructed with RNA Library Prep Kit for Illumina (E7760), and ribosomal RNA (rRNA) was deleted with the NEBNext rRNA Depletion Kit (E7405). Then, we sent the libraries to a sequencing facility for Illumina 6G sequencing. The raw read qualities were evaluated by FastQC.2.11.2Raw reads were filtered using Trimmomatic to remove low‐quality bases and adaptor sequences and then aligned to the GRCh38 human genome with GENCODE v29 gene annotation using STAR. Gene expression levels were calculated with FPKM values by normalizing gene counts from feature counts. All statistical analyses were performed in R.2.125C transferase reaction probes, nonreaction probes and negative control R‐Luc were converted (see above). Then, the target sequences of the m5C transferase reaction probes, nonreaction probes and R‐Luc were amplified by PCR and subjected to Sanger sequencing.Five hundred nanograms of in vitro m2.13The EZ‐Magna RIP kit (NO.17‐701) was used. Briefly, cells were lysed on ice with RIP lysis buffer. Then, 50 µl protein A/G magnetic beads, 100 µl cell lysis and 900 µl RIP buffer were added to a clean microtube and rotated at 4°C for 3 h. Ten microliters of cell lysate was kept as input and stored at −80°C. Finally, the RNA was purified, collected and converted to cDNA for qPCR.2.14The ChIP assay was performed with EZ‐Magna ChIP G . Briefly, the cell lysates were prepared with cell lysis buffer and nuclear lysis buffer with protease inhibitor cocktail II. Then, the cell lysates were ultrasonicated to break the genomic DNA into 200 ‐1000 bp pieces. After that, the treated cell lysates, antibodies and protein G magnetic beads were mixed and incubated at 4°C with rotation. Finally, the DNA fragments were purified and collected for qPCR and sequencing.2.15Each sample was harvested at 0, 3, 6, and 7 h after treatment with actinomycin D (2 µM). Total RNA was isolated and converted to cDNA for RT‐qPCR analysis.2.16The modification site sequence of AR was inserted downstream of the promoter of the pGL3‐promoter luciferase vector . C4‐2 cells were co‐transfected with a mixture of 2000 ng pGL3‐promoter‐AR‐Luciferase reporter vector and 1000 ng pRL‐TK vector. The relative luciferase activity was measured with a dual luciferase reporter assay system .2.17Biotin‐labelled RNA oligonucleotides were produced according to the above protocol. Recombinant human YBX1 proteins were purchased from Abcam (ab187443). The YBX1 proteins were mixed with probes in a binding buffer for 30 min at room temperature. The product was separated with 6% native PAGE gel and transferred to a nylon membrane. Membranes were then UV cross‐linked, blocked for 15 min, and incubated with HRP‐linked streptavidin (1:300) for 15 min. Add chemiluminescent substrate and incubate for 1‐3 min to expose with LAS 4 000 mini for 1‐5 min. The probe sequences were as follows: 5′‐cuuuccagaaucug……cugcugcugcagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcagcaagagacuagccccaggcagcagcagcagcagcagggugaggaugg……gccagcaaggggcugcc‐3′.2.18This study was approved by Fudan University (2020 FUSCC JS‐243). All treatments were administered according to the guidelines of the Institutional Animal Care and Use Committee.7 C4‐2  cells were mixed with Matrigel and injected into the backside of 6‐week‐old male BALB/cA nude mice. The animals were checked every 5 days. The tumours were weighed after the mice were sacrificed.A total of 102.19http://xena.ucsc.edu. Clinical data and gene expression profiles of 497 PCa tissues and 52 normal tissues were obtained. Besides, 88 high‐risk PCa patients enrolled from FUSCC, with pathology and electronic medical records provided. Samples of PCa and normal prostate tissues were collected during surgery or biopsy, then processed and stored at the FUSCC tissue bank.A total of 12 452 cancer patients with available level 3 RNA‐seq data were recruited from the TCGA database in the website: 2.20Primary antibodies against NSUN2, AR, AR‐V7, YBX1 and β‐actin were used for the immunoblot assay in this study. Detailed information is listed in Supporting Information.2.21t‐test, while categorical variables were compared with a χ2 test. All significance tests were two‐sided, and differences with a p‐value < .05 were considered significant. The cut‐off value was defined via median value or using the 'survminer' R package.Statistical analysis was performed with SPSS 22.0 software  and R. Continuous variables were compared with a 33.15C, 5‐methylcytidine).NSUN2 mRNA expression levels were significantly higher in 497 tumour samples than in 52 normal tissues  vectors. Colony formation assays revealed markedly fewer colonies when NSUN2 knocked down, consistently, more colonies when NSUN2 overexpression   , C4‐2 (castration‐resistant PCa cell) and C4‐2R n Figure . The CCKn Figure . Transwen Figure . The woun Figure . In the n Figure . Haematon Figure . IHC of ) Figure  and AR‐V) Figure . The IHC) Figure  and AR‐V) Figure  were mar) Figure  and weig) Figure  were mar3.35C fluorescence signal was significantly positively correlated with NSUN2 expression  and FOLH1 (known as prostate‐specific membrane antigen [PSMA]) at the transcriptional level by quantitative real‐time PCR (RT‐qPCR). The transcriptional levels of KLK3 and FOLH1 were decreased by siRNA‐mediated silencing of NSUN2  in C4‐2 cells and observed multiple unconverted cytosines near the end of the 5′‐UTR and start codon of AR   Figure . After t) Figure . The dott Figure . In ordes Figure . Mutateds Figure . Finallyp Figure  and was p Figure .3.5AR mRNA m5C modification, we first analysed the already known m5C 'readers,' YBX1 and ALYREF. As reported, ALYREF participates in mRNA export and YBX1 plays a role in mRNA stability.YBX1 expression and AR expression in the TCGA PRAD cohort (N = 497) indicated that YBX1 expression was positively correlated with AR expression . YBX1 could only bind m5C‐modified probes  is a newly developed AR antagonist.5C levels were dramatically decreased in a dot blot assay  dataset GDS4120), we found that t Figure . In FUSC2 Figure . These ay Figure . Consist120, we fs Figure  and apals Figure A,B. We ns Figure . Enzaluts Figure . In xenos Figure C–E. ThesNSUN2 transcription. So, we predicted the AR DNA‐binding motifs in the NSUN2 promoter sequences using the JASPAR database (http://jaspar.genereg.net).NSUN2  cohortp < .05). Most of these patients received first‐line second‐generation androgen receptor signalling inhibitor (ARSI) treatment. The progression‐free survival (PFS) after ARSI was plotted according to the level of NSUN2 expression. High NSUN2 expression significantly predicted poor PFS for 61 PCa patients from the MSKCC cohort  of mRNA to date.5C modification sites on mRNA are generally located in the translational start sites, 3′ untranslated regions (UTRs).5C sites were clustered in the 5′ end of AR mRNA and maintains the stability of AR mRNA. Traditional analysis of m5C modification sites used to ignore the cluster C signal for two reasons. First, false positives may occur due to incomplete bisulphite conversion in the GC‐rich sequence, which more easily forms secondary structures.5C site by point mutation is much easier than that of cluster m5C sites. In this study, we applied multiple experiments to illustrate that AR mRNA has a cluster of m5C modifications in the 5′‐end regions. We used Sanger sequencing and dot blot methods to illustrate this phenomenon. This study provides novel evidence that m5C modification clusters exist and have functions. Previously, a study reported that NSUN2 stabilizes CDKN2B/p16 mRNA.p16 in PCa is associated with poor DFS  AR‐V7+ rate was 8%.5C modifications exist on AR mRNA. NSUN2 can methylate AR pre‐mRNA and influence AR‐V7 expression, and YBX1 can bind and stable the m5C modified AR mRNA. AR can promote NSUN2 transcription. The NSUN2 and AR feedback loop leads to a poor outcome in PCa due to ARSI resistance. These findings suggest NSUN2 and YBX1 as new targets for the treatment of PCa.In conclusion, we found that mThe authors declare no conflict of interest.Supplementary Table 1: Clinicopathological parameters for 497 prostate cancer patients obtained from the Cancer Genome Atlas (TCGA).Click here for additional data file.Supplementary Table 2: Clinicopathological parameters for 88 high risk prostate cancer patients obtained from the Fudan University Shanghai Cancer Center (FUSCC).Click here for additional data file.Supporting InformationClick here for additional data file.Supplementary Figure 1 Analysis of NSUN2 and NSUN6 in the TCGA PRAD cohort.Click here for additional data file.Supplementary Figure 2 Wound healing assay of C4‐2 and C4‐2R and LNCaP cells with NSUN2 knockdown or OE. Representative images at 0 and 36 h are presented.Click here for additional data file.Supplementary Figure 3 NSUN2 influenced AR expression and acted as an oncogene.Click here for additional data file.Supplementary Figure 4 Positive control of the m5C‐RIP assay and the LC/MS/MS original data.Click here for additional data file.Supplementary Figure 5 Apalutamide could decrease NSUN2 expression.Click here for additional data file.Supplementary Figure 6 ChIP‐seq data for AR and H3K27ac profiling.Click here for additional data file.Supplementary Figure 7 The action of NSUN2 on p16 does not affect its promotion of prostate cancer.Click here for additional data file.Supporting InformationClick here for additional data file.


We benchmarked TaxiBGC on various simulated metagenomes, showing that our taxonomy-guided approach could predict BGCs with much-improved performance  compared with directly identifying BGCs by mapping sequencing reads onto the BGC genes . Next, by applying TaxiBGC on 2,650 metagenomes from the Human Microbiome Project and various case-control gut microbiome studies, we were able to associate BGCs (and their SMs) with different human body sites and with multiple diseases, including Crohn’s disease and liver cirrhosis. In all, TaxiBGC provides an in silico platform to predict experimentally characterized BGCs and their SM production potential in metagenomic data while demonstrating important advantages over existing techniques.Biosynthetic gene clusters (BGCs) in microbial genomes encode bioactive secondary metabolites (SMs), which can play important roles in microbe-microbe and host-microbe interactions. Given the biological significance of SMs and the current profound interest in the metabolic functions of microbiomes, the unbiased identification of BGCs from high-throughput metagenomic data could offer novel insights into the complex chemical ecology of microbial communities. Currently available tools for predicting BGCs from shotgun metagenomes have several limitations, including the need for computationally demanding read assembly, predicting a narrow breadth of BGC classes, and not providing the SM product. To overcome these limitations, we developed IMPORTANCE Currently available bioinformatics tools to identify BGCs from metagenomic sequencing data are limited in their predictive capability or ease of use to even computationally oriented researchers. We present an automated computational pipeline called TaxiBGC, which predicts experimentally characterized BGCs (and infers their known SMs) in shotgun metagenomes by first considering the microbial species source. Through rigorous benchmarking techniques on simulated metagenomes, we show that TaxiBGC provides a significant advantage over existing methods. When demonstrating TaxiBGC on thousands of human microbiome samples, we associate BGCs encoding bacteriocins with different human body sites and diseases, thereby elucidating a possible novel role of this antibiotic class in maintaining the stability of microbial ecosystems throughout the human body. Furthermore, we report for the first time gut microbial BGC associations shared among multiple pathologies. Ultimately, we expect our tool to facilitate future investigations into the chemical ecology of microbial communities across diverse niches and pathologies. Staphylococcus aureus (MRSA) and vancomycin-resistant Enterococci (VRE)   are a group of low-molecular-weight, structurally diverse, and bioactive chemical compounds –3. Altho–4–8–13–ci (VRE) .The genes mainly responsible for synthesizing, modifying, and exporting SMs in microbes are often found in biosynthetic gene clusters (BGCs). In brief, BGCs are physically clustered groups of genes in a microbial genome that encode a biosynthetic pathway for producing an SM and its chemical variants , 21. WitEarly computational tools to detect BGCs from microbial genomes , an easy-to-use, command-line tool that identifies experimentally characterized BGCs from shotgun metagenomic data and infers their known SM products. TaxiBGC does not require genome assembly and can be applied to any metagenome. Importantly, our novel approach enables the prediction of experimentally characterized BGCs by first considering the microbial species from which they are derived, thereby allowing the user to trace the predicted and likely taxonomic origins of BGCs.Realizing the limitations mentioned above, we set out to develop a method that accurately and rapidly detects known BGCs from real-world, complex microbiomes. Herein, we introduce Taxonomy-guided Identification of Biosynthetic Gene Clusters) is a computational strategy for predicting experimentally characterized BGCs and their annotated SMs in shotgun metagenomic sequencing data. The TaxiBGC pipeline consists of three major steps (in silico confirmation of the predicted BGCs (from the second step) based on read mapping  using BBMap  using a range of BGC gene presence and BGC coverage thresholds. We obtained prediction accuracy (F1 scores) by comparing the predicted BGCs with the actual BGCs comprising the simulated metagenomes. The pair of thresholds yielding the highest mean F1 score after testing on all 125 simulated metagenomes was selected as the optimal minimum BGC gene presence and BGC coverage cutoffs for TaxiBGC.In our study, the presence of a BGC gene was determined based on the fulfillment of a minimum percentage length of that gene mapped onto by metagenomic reads; and the coverage of a BGC was defined as the proportion of its total number of genes that were found to be present in the metagenome. We determined a set of optimal BGC gene presence and BGC coverage thresholds for the TaxiBGC pipeline based on their overall predictive performance on 125 simulated metagenomes of mock microbial communities . These sThe TaxiBGC reference database essentially provides information linking experimentally characterized BGCs and their corresponding SMs with their source organism . This database, which is relied on by the TaxiBGC pipeline during BGC prediction , is predIn all, the TaxiBGC reference database encompasses 390 unique BGC-harboring microbial species, 953 unique experimentally characterized BGCs, and 1,169 total  SMs. Of note, a BGC can be derived from multiple species, a BGC can encode multiple SMs, and more than one BGC can encode for the same SM. BGCs encoding nonribosomal peptides (NRPs) are the most prevalent among the 390 species ; followed by polyketides ; ribosomally synthesized and posttranslationally modified peptides (RiPPs) ; others, i.e., not part of the six main categories provided in the MIBiG database and therefore collectively grouped into a single class ; saccharides ; terpenes ; and alkaloids  (we followed the MIBiG standard notations for the major SM structure-based classes). BGCs, along with their classes/subclasses, and the taxa from which they are derived are described in detail in Escherichia coli), 22 (Aspergillus nidulans), or 23 (Streptomyces griseus); among all species, 217 (55.6% of 390) harbor only one BGC ; and concerning a BGC being present, at least a minimum proportion of its constituent genes should be present . On simulated metagenomes, of which the BGC compositions are known, TaxiBGC prediction performance was evaluated over a range of these thresholds . More specifically, a total of 400 pairs of thresholds for BGC gene presence (5 to 100% in increments of 5%) and BGC coverage (5 to 100% in increments of 5%) were tested on a total of 125 simulated metagenomes. The predicted BGCs were then compared with the actual BGCs to obtain prediction accuracy.In TaxiBGC, identifying whether a BGC is present (or not) in a metagenome is dependent mainly on the following two criteria: regarding a 1 score, 0.56) for predicting BGCs in all simulated metagenomes was achieved with a minimum BGC gene presence threshold of 5% and a BGC coverage threshold of 10%  when calculated with these optimal thresholds  were found to be very close to the F1 scores found when using the pair of thresholds most accurate for each metagenome, which can vary sample to sample  reads compared to those with 40 million and 80 million reads   . Second,10.1128/msystems.00925-22.6TABLE S4Table S4, XLSX file, 0.01 MB.Mean relative abundances of BGC-harboring species in each simulated metagenome. Download Copyright © 2022 Gupta et al.2022Gupta et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 1 score of 0.49   . To demonstrate the predictive capability of this direct BGC detection approach, we again tested a range of BGC gene presence and BGC coverage thresholds  on the same 125 simulated metagenomes utilized above . From all possible pairwise combinations of thresholds, we found that a minimum BGC gene presence of 5% and a minimum BGC coverage of 90% led to the best mean F U test) . Moreove U test) , indicat10.1128/msystems.00925-22.1FIG S1FIG S1, TIF file, 1.3 MB.Predictive performance of the direct BGC detection approach based on two different thresholds. The direct BGC detection method was used to predict BGCs in all 125 simulated metagenomes of mock microbial communities. We used 400 total pairwise combinations of BGC gene presence (5 to 100% in increments of 5%) and BGC coverage (5 to 100% in increments of 5%) thresholds. The best overall accuracy for predicting BGCs in simulated metagenomes was achieved with a minimum BGC gene presence and BGC coverage of 5% and 90%, respectively . Download Copyright © 2022 Gupta et al.2022Gupta et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the To demonstrate the utility of TaxiBGC, we applied our novel approach on 1,217 metagenome samples from the Human Microbiome Project (HMP-1-I and HMP-1-II) , 38. The10.1128/msystems.00925-22.7TABLE S5https://doi.org/10.1038/nature11234) and HMP-1-II  metagenomes used for TaxiBGC demonstration. Download Table S5, XLSX file, 0.1 MB.HMP-1-I . Most (20 of 24) BGCs were exclusive to a particular body site , while four BGCs encoding for an exopolysaccharide (BGC0000764), nisin A (BGC0000535), nisin O (BGC0001701), and ruminococcin A (BGC0000545) were found to be present in more than one body site.Across all five body sites, we identified a total of 24 unique BGCs present in at least one sample . FourteeP < 0.001, Fisher’s exact test) but only for 40 (or 7.9%) of the total 505 samples. Mutacin K8 is a major lantibiotic bacteriocin produced by Streptococcus mutans, which is a key bacterium for the formation of dental plaques. It has been shown to have potent activity against other streptococcal species in the oral cavity ; this BGC was predicted in 35 (or 7.4%) and 1 (or 3.9%) of the 472 gut microbiome and 26 skin microbiome samples, respectively. Lastly, BGCs for gassericin E (BGC0001388), gassericin S (BGC0001601), and gassericin T (BGC000619) were predicted exclusively in the vaginal microbiome  for 19 (or 19.4%), 4 (or 4.1%), and 18 (or 18.4%) of the total 98 samples, respectively. A study showed that gassericin E, which was produced by Lactobacillus gasseri EV1461 isolated from the vagina of a healthy woman, inhibited the growth of pathogens associated with bacterial vaginosis , thereby associating BGCs and their SM production potential with human diseases.We can also demonstrate TaxiBGC in the context of translational research to find BGCs associated with clinical phenotypes of interest. We applied TaxiBGC on 1,433 gut microbiome  samples from the following nine published case-control studies: three Crohn’s disease (CD) studies 4345, four 46–10.1128/msystems.00925-22.8TABLE S6Table S6, XLSX file, 0.2 MB.BGCs predicted by using TaxiBGC on stool metagenomes collected from published case-control studies. Download Copyright © 2022 Gupta et al.2022Gupta et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the In the study involving gut microbiomes from patients with LC and controls, ten BGCs were significantly different in proportions between LC patients and controls , as follSix BGCs were identified in significantly different proportions between patients with CD and controls . Five BGFour BGCs were found to be associated with CRC . Three gInterestingly, five of the disease-associated gut microbial BGCs mentioned above were shared across multiple gastrointestinal diseases. For example, BGC0001701 encoding nisin O was found more often in controls than in LC, CD, and CRC  constructed using varied combinations of species identities, species richness, and sequencing library sizes. Accordingly, we showed that BGC prediction using our taxonomy-guided approach  was superior to directly mapping reads onto BGC genes . Next, to identify BGCs (and thereby being able to estimate their corresponding SMs) associated with human health and disease, we demonstrated our TaxiBGC pipeline on metagenomes sampled from different body sites and on gut microbiomes collected from patients with liver cirrhosis, rheumatoid arthritis, Crohn’s disease, or colorectal cancer. Our results show that human body sites harbor distinct microbial BGC signatures, which mostly encode bacteriocins. Furthermore, by characterizing the potential chemical milieu of the gut microbial environment for different diseases and their controls, our results provide a starting point for discovering stool-borne SM biomarkers and therapeutic leads.Accurately predicting the biosynthetic potential of BGCs from microbiomes is currently one of the most important challenges in microbial natural product research. Here, we present TaxiBGC, a computational pipeline for predicting experimentally characterized, microbial BGCs with their known SMs in shotgun metagenomes. TaxiBGC employs the following three main steps for predicting BGCs: (i) identification of BGC-harboring species, (ii) initial prediction of BGCs based on the identified BGC-harboring species, and (iii) Several limitations of TaxiBGC should be noted when interpreting our results. First, by design, BGC prediction by TaxiBGC relies on the successful identification of microbial species from metagenomes. In the case where MetaPhlAn3 (or other taxonomy profiling tools in future versions of TaxiBGC) cannot identify all the BGC-harboring species, TaxiBGC would not be able to accurately predict the entire breadth of BGCs. Second, predictions regarding the taxonomic origins of BGCs need to be interpreted with caution. This call for caution is because, in the “mixed bag of genes” context of metagenomes, gene elements of a particular BGC could originate from other BGCs and multiple species. Nevertheless, TaxiBGC can spark new and exciting hypotheses regarding the connections between microbiome BGCs and their source species, which can be validated in future empirical studies. Third, although the taxonomy-guided step in our approach can certainly reduce false-positive BGC predictions relative to true positives, the trade-off is that we may miss BGCs that are present in the metagenomes, thereby leading to type II errors . Fourth, TaxiBGC provides only the chemical family—but not the specific molecular structure—for a small number of SM products, such as glycopeptidolipid and exopolysaccharide. This limitation is simply because more detailed information is not yet available in MIBiG. Fifth, TaxiBGC is designed to predict only known BGCs whose SMs have been verified by other research groups. Therefore, its predictions do not extend to putative  BGCs that have yet to be isolated and expressed in bacterial hosts. Finally, experimental verification of whether the BGCs (and their SMs) reported here are indeed implicated in health outcomes, e.g., either maintaining the structure of the so-called “healthy” gut microbiome , 55, 56 Despite the limitations mentioned above, TaxiBGC provides several advantages over currently available tools for BGC identification. First, TaxiBGC employs an assembly independent, read-based prediction method; this method solves a fundamental limitation of current BGC prediction tools that assume each BGC is encoded within a single contig in the genome or assembled metagenome, whereas in reality, genes of BGCs can be dispersed throughout several contigs. Second, TaxiBGC can be used to associate BGC presence with species abundance, which can help pinpoint which BGCs originate from which species under different phenotypic conditions. Third, TaxiBGC can simultaneously identify several classes of experimentally characterized BGCs in a metagenome sample. This comprehensive and unbiased detection is essential to deepen our understanding of the diversity of known BGCs and their SMs in a microbiome. Fourth, no parameter selection or optimization is necessary before running TaxiBGC. The only preinstalled software needed in TaxiBGC is MetaPhlAn3 for taxonomic species identification and BBMap v38.90 (or higher) for mapping metagenomic reads onto BGC genes.In closing, we anticipate that TaxiBGC can facilitate the unbiased identification of experimentally characterized BGCs and their annotated SMs from shotgun metagenomes. It is also worth noting that TaxiBGC is not limited to the use in human microbiomes but can easily be applied to solve questions in other types of microbiomes  for BGC identification. Additionally, we envision that our novel pipeline can contribute to our ongoing efforts to computationally model the wide range of potential metabolite-driven interactions within complex microbial communities –59. Fina–Simulated metagenomes were constructed according to the following steps. First, 25 metagenome samples were selected randomly from the Human Microbiome Project (HMP) , 38. Sec10.1128/msystems.00925-22.2FIG S2FIG S2, TIF file, 1.7 MB.Relative abundances of strains in each simulated metagenome. The rank-plot shows (in descending order of magnitude) the relative abundances of all strains in each simulated metagenome. The mock microbial communities used to construct simulated metagenomes are composed of 39 to 105 unique strains, resulting in 39 to 97 unique species. SM, simulated metagenome. Download Copyright © 2022 Gupta et al.2022Gupta et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/msystems.00925-22.9TABLE S7Table S7, XLSX file, 0.06 MB.Relative abundances of strains (of species) in each mock microbial community used for constructing simulated metagenomes (SMs). Download Copyright © 2022 Gupta et al.2022Gupta et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the 10.1128/msystems.00925-22.10TABLE S8Table S8, XLSX file, 0.01 MB.Number of BGC-harboring and non-BGC-harboring microbial species in simulated metagenomes. Download Copyright © 2022 Gupta et al.2022Gupta et al.https://creativecommons.org/licenses/by/4.0/Creative Commons Attribution 4.0 International license.This content is distributed under the terms of the in silico confirmation of those predicted BGCs, genes of those BGCs were searched for in the metagenomes using BBMap v38.90  , this ap1 score, defined as the harmonic mean of precision and recall, is calculated as follows:The FTP (true positives) is the number of BGCs that were correctly predicted to be present; FP  is the number of BGCs that were incorrectly predicted to be present; and FN  is the number of BGCs that were missed, i.e., incorrectly predicted to be absent by TaxiBGC.Here, for a given metagenome, Metagenome samples from the following were excluded from the current study: (i) subjects undergoing dietary/medication interventions, (ii) metagenome samples with less than 5 million reads, (iii) metagenome samples sequenced as single-end reads, and (iv) samples collected from patients with comorbidities. In the case where multiple runs were available for a sample, only the sequencing run with the highest read count (of at least 5 million reads) was included for analysis. If multiple samples were collected from the same individual across different time points, then only the sample collected at the first recorded time point was considered. In all, the TaxiBGC pipeline was applied on 2,650 publicly available, human-derived metagenomes from 11 independent published studies. Raw sequence files of all metagenomes were downloaded from the NCBI Sequence Read Archive.https://anaconda.org/danielchang2002/TaxiBGC). The source code, MIBiG BGC gene sequences, the TaxiBGC reference database, and complete instructions for installation and usage are freely available online at https://github.com/danielchang2002/TaxiBGC_2022.TaxiBGC is an open-source command-line tool that is implemented in Python and bash. To avoid dependency conflicts, TaxiBGC can be installed via Anaconda (


To illustrate a surgical technique for augmented reality (AR)-assisted unicompartmental knee arthroplasty (UKA) and report preliminary data.We developed an AR-based navigation system that enables the surgeon to see the tibial mechanical axis superimposed on the patient’s leg in addition to the tibial cutting angle. We measured the tibial resection angle in 11 UKAs using postoperative radiographs and calculated the absolute difference between preoperative target angle and postoperative measured angle. The target angle was determined for each patient: mean values were 0.7° ± 1.0° varus in coronal alignment and 5.3° ± 1.4° posterior slope in sagittal alignment.The angles measured on postoperative radiographs were 2.6° ± 1.2° varus in the coronal plane and 4.8° ± 2.5° posterior slope in the sagittal plane. The absolute differences between the target and measured angles were 1.9° ± 1.5° in coronal alignment and 2.6° ± 1.2° in sagittal alignment. No patients experienced complications, including surgical site infection and periprosthetic fracture.The AR-based portable navigation system may provide passable accuracy in terms of proximal tibial resection during UKA.IV Unicompartmental knee arthroplasty (UKA) is an attractive option to treat unicompartmental end-stage knee osteoarthritis and osteonecrosis . Accuratimage-based large-console navigation, imageless large-console navigation, and portable navigation [Computer-assisted navigation systems have contributed to improvement of the accuracy of bone cutting in knee arthroplasty. These navigation systems can be divided into three groups: vigation . Both imvigation . The survigation .Augmented reality (AR) technology shows great promise in computer-assisted surgery due to its unique ability to fuse live images and synthetic computer-generated images , 8. We dThis retrospective single-arm cohort study was approved by the institutional ethics board. We reviewed 11 consecutive UKAs performed using the AR-based portable navigation system to proximal tibial resection between January 2020 and November 2021. All patients provided written informed consent.All surgeries were performed by one surgeon (ST) using a Persona Partial Knee System . Tibial bone resection was performed using the AR-based portable navigation system. The target angle of tibial resection was determined for each patient using the original varus angle and posterior slope of the proximal tibia as references. In the coronal plane, we aimed to resect the proximal tibia perpendicular to the mechanical axis of the femur except in patients with preoperative varus angle of the proximal tibia ≥ 6°, in whom we set the target varus angle to 2° or 3° because varus alignment exceeding 4° was reported to be associated with translation in the mediolateral direction . In the The tibial resection angle was measured using a standing long-leg radiograph with ImageJ software . The coronal alignment was measured with reference to the perpendicular line connecting the midpoint of the tibial plateau and the midpoint of the tibial plafond . The sagAR technology projects digital information onto the real world , 12. TheThe extramedullary tibial cutting guide of the AR-based navigation system carries two markers with Quick Response (QR) codes Figs.  and 2. TThe sensor of the AR-based navigation system is the camera of the smartphone. The smartphone camera recognizes the QR code of the extramedullary tibial cutting guide. Using a pointer marked with a QR code, the surgeon registers three bony landmarks: the most prominent point of the medial malleolus, the most prominent point of the lateral malleolus, and the tibial center on the tibial plateau Fig. . VisualiAfter completing registration, the AR-based navigation system enables the surgeon to view the reference lines superimposed on the tibia on their smartphone display Fig. . The surAfter tibial bone resection, the AR-based navigation system allows the surgeon to verify the actual cutting angle and depth of resection. The display of the smartphone shows varus/valgus angle, tibial slope angle, rotation angle, and the thickness of bone resection Fig. .Fig. 5VeThe patient characteristics and results of radiographic measurement of the patients are summarized in Table With regard to coronal alignment, the mean ± standard deviation of postoperative varus angle was 2.6° ± 1.2°. With regard to sagittal alignment, postoperative posterior slope angle was 4.8° ± 2.5°.The absolute differences between the preoperative target resection angles and postoperative measured angles were 1.9° ± 1.5° in coronal alignment and 2.6° ± 1.2° in sagittal alignment.No patients experienced complications, including surgical site infection and periprosthetic fracture.We reported the surgical technique of AR-based portable navigation for tibial bone resection during UKA. AR technology has attracted increasing interest in surgical practice . In orthThere are several advantages to using AR-based portable navigation for UKA. First, the AR-based navigation system can visualize the mechanical axis and registration points. Other navigation systems do not have this capability. The visualization may be useful not only for enhancing accuracy of surgical procedures, but also in surgical education for inexperienced surgeons.Second, the running costs for use of the AR-based portable navigation in UKA are low. The AR-based navigation system can be used with an application downloaded to the surgeon’s own smartphone, several QR code markers, and the dedicated extramedullary guide. In addition, neither an assistant nor additional equipment is required in the nonsterile zone because the operation of the AR-based navigation system is accomplished by the surgeon in the sterile zone alone.Third, no extra pins are needed to use the AR-based navigation system in UKA because the extramedullary cutting guide carries QR codes for registration. Pinholes located in the proximal tibial plateau are associated with risk of periprosthetic fracture . TherefoThis study had several limitations. First, this was a preliminary study in a single-arm cohort with small sample size. Although a pilot study was crucial to assess the feasibility of a larger comparative study, it must be noted that this study could not conclusively demonstrate the clinical effectiveness of the AR-based navigation system. Second, the results lack generalizability because all surgeries were performed by a single surgeon at a single institute, and surgeon’s experience has been shown to affect the clinical and radiographic outcome of UKA .The AR-based navigation system may be an effective option to enhance the accuracy of tibial bone resection during UKA. This preliminary study provided important information for future studies to investigate the clinical effectiveness and safety of the AR-based navigation system.


The BMI differed significantly according to headache severity (p ˂ 0.001). The most common allergen was “dust or mites” (41.1%). Acetaminophen (35.9%) was the most commonly used painkiller. The coexistence of AR and headache may indicate that these conditions share a similar pathophysiology. Better management of allergies may facilitate diagnosis, treatment, and prophylaxis of headaches.Headache and allergic rhinitis (AR) are common in children and often co-occur. We investigated the clinical characteristics of pediatric headaches and the association of AR and chronic headaches. We retrospectively reviewed the medical records of patients admitted to our pediatric inpatient and outpatient clinics with complaints of headache between January 2017 and June 2020 for headache-specific history, AR signs and symptoms, allergy skin prick test, inhalant multiple allergen simultaneous test results, laboratory and imaging findings, and medication history. The patients were divided into three subgroups: AR, non-AR, and headache groups, reporting 45.7% patients with headache alone, 13.7% with additional AR, and 31.6% with abnormal imaging findings, suggesting that headache was combined with sinusitis (24.3%) or mastoiditis (7.3%). Furthermore, 6% of the patients had both AR and sinusitis. Body mass index (BMI) differed significantly between the AR and the non-AR and headache groups ( Headaches are common among children and adolescents, and they can persist into adulthood . The IntNumerous studies have examined the association between migraine and allergies, although the correlation between these two conditions remains controversial . We analThis retrospective study was conducted at the Department of Pediatrics of Yeungnam University Hospital in Daegu, Korea. Between January 2017 and June 2020, 412 patients were admitted with headache as their presenting symptom.In this study, patients were enrolled according to their headache symptoms. Therefore, not only primary headache such as migraine but all headaches were included. Chronic headaches were defined as headaches longer than 3 months according to the international classification of headache disorders third edition . Their mAgeSexBody Mass Index (BMI)Headache-specific history: Time of onset, duration, and severity Associated allergic disease: Atopic dermatitis, asthma, allergic conjunctivitisSymptoms of rhinitis: Nasal congestion, sneezing, itching, rhinorrheaFamily history Medical background Treatment and clinical outcomesMedical recordsLaboratory results: White blood cell (WBC) count, hemoglobin (Hb), platelet (PLT), aspartate aminotransferase (AST), alanine aminotransferase (ALT), blood urea nitrogen (BUN), creatinine (Cre), sodium (Na), potassium (K), and total Immunoglobulin E (IgE) levels.Allergy test: skin prick test (SPT), inhalant multiple allergen simultaneous test , and screening for common allergens .Imaging data: Brain magnetic resonance imaging (MRI), brain computed tomography (CT), and X-ray paranasal sinus (PNS) series and water view.Examination datap-value < 0.05 was considered statistically significant.All statistical analyses were performed using IBM SPSS ver. 25.0 software . Quantitative data were compared using ANOVA. The Kolmogorov–Smirnov test was used to confirm that the data follow normality, and a parametric statistical method was used. Correlations among the groups were determined using Fisher’s exact test. Values are presented as means ± standard deviations, and a p = 0.831). Furthermore, 31.6% of all patients had sinusitis, and 6% had both AR and sinusitis. The mean age of the study population was 11.37 ± 3.52 years; there was no significant difference among the groups (p = 0.861). The BMI differed significantly between the groups (p = 0.03). In the AR group, the BMI was 22.19 ± 5.11 kg/m2, which was greater than that in the non-AR (20.41 ± 3.42 kg/m2) and headache groups (20.17 ± 3.76 kg/m2)  . We inve6 kg/m2) .n = 163) or mastoiditis (n = 17)  . Most ca(n = 17) .p = 0.522) or sinusitis (p = 0.927). However, BMI affected the headache severity significantly (p < 0.001) , followed by pollen (28.6%), animal dander (23.2%), and mold (7.1%) . We acce< 0.001) . Acetami< 0.001) . With thA headache is a universal human experience. A primary headache is diagnosed when there is no obvious disease or structural problems associated with the headache. Common primary headache disorders defined by IHS include migraine and tension-type and cluster headaches. A secondary headache is one that is caused by an underlying disease. Infection, head injury, vascular disorders, brain hemorrhage, and tumors are among the different causes of secondary headache ,16. AddiAR is a prevalent and persistent childhood illness . Associap ˂ 0.001). However, no significant relationship was found between headache severity and AR (p = 0.522) or sinusitis (p = 0.927).Imaging revealed that the majority of sinusitis cases involved the ethmoidal and maxillary sinuses; 6% of the patients had both AR and sinusitis. BMI significantly affected headache severity (According to reports, the majority of patients who present with “sinus headache” have migraine . The IHSAR is an IgE-mediated phenomenon involving the activation and degranulation of mast cells and basophils and often causes “sinus headache”. Histamine is a key inflammatory mediator released during degranulation, and the nasal mucosa is in close proximity to the CNS vasculature. Thus, AR and migraine share similar neural pathways .Several clinical studies have shown that nasal endoscopic findings yield objective evidence of nasal congestion and rhinorrhea during migraine attacks. As is true of AR, midfacial or nasal pain during migraine may be accompanied by the release of a variety of neuropeptides, such as histamine, substance P, NO, vasoactive intestinal peptide, TNF-α, and others . Many prThe most commonly used analgesics for headache pain include aspirin, naproxen, ibuprofen, acetaminophen, combinations of these agents, triptans, and opioids . In the Obesity is associated with chronic daily headaches . Both heThe most commonly used analgesics for headache pain include aspirin, naproxen, ibuprofen, acetaminophen, combinations of these agents, triptans, and opioids . In the Our study has some limitations. This study was a retrospective study, and due to the different financial status and age of patients, the type and number of instrumented examinations were different. Sensitivity of the skin prick test and MAST are different, which may have affected the results . PatientIn our study, we found no association between headaches and AR. However, recent studies support the idea that headaches and allergic diseases are correlated ,32. In t


The topics address problems of classical (CL) and quantum (QU) statistical physics. As for the CL side, these comprise: multistability and ergodicity breaking; the formation of dissipative  structures in a nonequilibrium bath; ion-influenced conformation of biopolymers (glycosaminoglycans) near biosurfaces; infectious-disease propagation in terms of social distancing; far-from-equilibrium information processing employing networks of chemical oscillators; and a problem of equivalence of the Carnot principle to the second law of thermodynamics, and non-equivalence to the first Clausius and Kelvin principles. As for the QU side, in turn, these include: mixedness, coherence and entanglement in three-qubit states; (anti)coherence caused by a thermal bath; and finally, quantum graphs split at vertices as simulated experimentally by using microwave networks. All contributions can be united under the common flagship of maximum-entropy and entropy production principles experienced by the respective CL and QU systems in (non)equilibrium conditions.This Special Issue collected ten papers addressing a range of topics in condensed matter and interdisciplinary classical vs. quantum physics. All of them are linked together by statistical physics/mechanics methods. The selection emerged from a survey of topics presented at the XLVII Congress of Polish Physicists held in Bydgoszcz, Poland on the 19–23 September 2021 ) as a hybrid event, gathering in total more than two hundred fifty regular participants and more than forty invited speakers. Amongst them, one may find the name of a Nobel Prize winner (2004), Professor Frank Wilczek, with his special online contribution titled “Time Crystals”. Over the course of five days and around fifteen sessions, covering topics ranging from physics’ teaching and popularization, the history of physics, and general physics to the physics of high energy and cosmology, gravitation, and astrophysics, the participants presented their recent contributions to the field. One of those sessions was titled Statistical, Nonlinear and Complex Systems’ Physics, whereas the other one, relevant for this Special Issue (SI), was the session titled Condensed Matter Physics.  However, from these two sessions, one may expect to have a topical reflection contained in the overarching SI.The XLVII Congress of Polish Physicists was, for the first time in over hundred years in the history of the Polish Physical Society, held in Bydgoszcz, Poland on the 19–23 September 2021 crystals. It can be so taken when looking at it from the first side. However, a closer inspection of the SI material gives rise to a much more monodispersive/single-crystal and compacted (than crudely expected) picture of the SI contents presented to a potential reader. Namely, all contributions collected can be united under the common denominator of maximum-entropy and entropy production principles experienced by both classical (CL) and quantum (QU) systems in (non)equilibrium conditions. In what follows, let us unveil the main messages conveyed by the ten collected papers of the SI. The proposed order of presenting the material commences with properly subordinated CL systems (seven contributions) and ends up with three remaining QU systems, presented by their authors.The paper “Velocity Multistability vs. Ergodicity Breaking in a Biased Periodic Potential”  investigIn the paper titled “Accumulation of Particles and Formation of a Dissipative Structure in a Nonequilibrium Bath”  it is deIn the study “Spherulites: How Do They Emerge at an Onset of Nonequilibrium Kinetic-Thermodynamic and Structural Singularity Addressing Conditions?” , the autThe proposal of a prerequisite of a (paradigmatic) chemical computer is discussed in “Information Processing Using Networks of Chemical Oscillators” . It is a+, Mg2+ and Ca2+), on human serum albumin–hyaluronan/chondroitin-sulfate interactions examined by means of molecular docking followed by molecular dynamics simulations. A certain type of glycosaminoglycan binding is analyzed by using a conformational entropy approach, and several protein–polymer complexes are studied to inspect, specifically, how the binding site and presence of ions influence their affinity conditions.Another paper collected by the SI which refers to CL systems, “Effect of Ion and Binding Site on the Conformation of Chosen Glycosaminoglycans at the Albumin Surface” , tacklesThe next CL-type paper  of the oAnother paper from the CL collection, “Proof of Equivalence of Carnot Principle to II Law of Thermodynamics and Non-Equivalence to Clausius I and Kelvin Principles” , covers The paper titled “Mixedness, Coherence and Entanglement in a Family of Three-Qubit States”  regards The second from the small series of QU papers, “Coherence and Anticoherence Induced by Thermal Fields” , addressThe last in-presentation-order (QU) paper of the SI “The Generalized Euler Characteristics of the Graphs Split at Vertices”  argues tTo summarize, this SI has focused on relevant and fundamental issues of statistical classical/quantum physics (and related subdisciplines), pointing to maximum-entropy and entropy production (and/or the spread of information) principles experienced by the respective CL and QU systems in (non)equilibrium conditions. The studies ,7,8,9,10