A positive detection of VZV antigen was statistically associated in the epidermis with recent SV and in the dermis with long‐lasting SV (p = .001). Finally, the discovery of mature virions in 3/3 recent SV samples provides additional arguments for our viral hypothesis.Segmental vitiligo (SV) is a unilateral subtype of vitiligo which is clinically characterized by a cutaneous depigmentation and histologically by a melanocyte loss from the epidermis and hair follicle reservoirs. To date, its pathogenesis remains a mystery. In many cases, this skin depigmentation shares several clinical features and dysfunctions with herpes zoster (HZ). So, for the first time, we examined whether any nucleus and cell fusion associated with a positive immunolabelling of varicella‐zoster virus (VZV) and VZV mature virions could be found in SV skin samples as in herpes zoster (HZ). A total of 40 SV samples were used for histological and immunochemical studies. Control samples were obtained from three HZ, and 10 generalized vitiligo lesions. For ultrastructural study, three recent SV and one HZ as controls were recruited. Here, we report that nuclear fusion in epidermal cells were statistically associated with recent SV ( A possible role of VZV in SV pathogenesis could be evoked following the concomitant discovery in the same melanocytes of characteristic mature VZV virions, perinuclear clustering, and lysis of mature melanosomes. These abnormal distribution and degradation of melanosomes were previously reported in several lysosomal diseases due to various gene mutations and were attributed to a defective transport and transfer of mature melanosomes to keratinocytes. Therefore, in SV, an inhibition of normal melanosome trafficking in melanocytes following a local virus infestation could be the first step of a cascade of events leading to a depigmentation and possibly to an autoimmune process.1Segmental vitiligo (SV) is a subtype of vitiligo characterized by a progressive and unilateral cutaneous depigmentation due to a melanocyte loss from both epidermis and hair follicle reservoirs , we can mention the following features:Varicella‐zoster virus is a ubiquitous human alpha‐herpesvirus that infects and becomes latent not only in the cranial and spinal sensory and enteric ganglia but, also, in autonomic ganglia during viremia with varicella. VZV can commonly reactivate in sensory ganglia many years after primary infection to cause HZ Strauss, , but it In zoster without rash , mean age 30.4 ± 10.5 SD, three herpes zoster, and five healthy skin samples, mean age 28.3 ± 11 SD were recruited from August 2019 to January 2021 Table : With CLn = 13; onset of the disease ≤4 months), melanocytes appeared heavily pigmented around the nucleus and sometimes loaded with giant melanin granules in the cytoplasm and within the dendrites , marginal melanocytes with cell or nuclear fusion were seen  , , no melanocyte was found in the depigmented areas of SV patients. Whereas, in the pigmented edge of recent SV  Figure . In long, Figure . In the p = .0004)  , and between syncytia and VZV dermal staining .A strong positivity of VZV immunolabelling  was detected in all three HZ skin samples Figure . Anti‐VZ) Figure . In rece) Figure . On the ) Figure . These iHistologically and immunochemically, the expression of cytopathic changes and immunolabelling against VZV appears depending on the age of SV lesions. So, at the initial period, the perinuclear clustering of melanosomes could correspond to a positive immunolabelling by early viral structural (IE 63) and late proteins in some epidermal cells  on 3 SV samples. In one HZ sample, used as VZV infection control, abundant virus particles including capsids, nucleo‐capsids, and characteristic VZV mature virions were easily detected by transmission electron microscopy  was involved in analysis and interpretation of histological and ultrastructural data and in writing the manuscript. S. Lepreux (Pathologist) have made contribution to the histological, immunochemical, and ultrastructural studies. M. Cario  was involved in the examination and analysis of immunochemistry and electron microscopy, data analysis, and in the writing of manuscript. J Rambert (Electron microscopy) was involved in the examination of sections for electron microscopy. M. Lafon (Virologist) was involved in critically revising the manuscript and in trials of PCR assessment in SV skin samples. A. Dakdaki (Molecular Biology) have made contribution to the immunochemical study. R. Abouqal  was involved in statistical study of histological and immunochemical data. L. Benzekri  was involved in recruitment of patients, in performing biopsies and made substantial contributions to the conception and the writing of the manuscript. Dr Y. Gauthier and Pr L. Benzekri contributed equally to this article.None.The authors declare that they have no conflict of interest.Informed consent was obtained from all individual participants.Figure S1Click here for additional data file.Figure S2Click here for additional data file.Figure S3Click here for additional data file.Figure S4Click here for additional data file.Figure S5Click here for additional data file.Table S1Click here for additional data file.


To statistically study the 3D shape of oesophageal cancer (EC) and its spatial relationships based on computed tomography angiography (CTA) 3D reconstruction, to determine its relationship with T‐stages, and to create an optimal T‐stage diagnosis protocol based on CTA calculation.t‐test, ROC, etc., were performed and critical values between different T‐stages were calculated. We also invited two radiologists to evaluate the measurements.Pre‐operative CTA images of 155 patients with EC were retrospectively collected and divided into four groups: T1–T4. We used Amira software to segment and 3D reconstruct the EC, oesophagus, aorta, pericardium and peripheral lymph nodes and measured their surface area, volume, major axis, minor axis, longitudinal length, roughness and relationship to the aorta of the EC. One‐way ANOVA, independent sample 3 separately (p < 0.05), and the T1–T4 volume cut‐off values were 11,712.00, 19,809.00 and 44,103.50 mm3 separately. For comparison with radiologists, the AUC value of our measurements was 0.704, which was higher than the radiologists of AUC = 0.630.There were no significant differences in EC longitudinal length, roughness score and relationship with the aorta between the different T‐stages of EC. There were significant differences in EC surface area, EC volume and mean major and minor axis among the different T‐stages. The volumes of the T1–T4 tumours were 12,934.36 ± 7739.25, 23,095.27 ± 14,975.67, 37,577.98 ± 36,085.64 and 58,579.25 ± 41,073.96 mmEC volume, major and minor axis can be used as important factors for surgeons in the T‐stage diagnosis of EC, which helps to improve prognosis and treatment decisions after CTA. Inclusion criteriap > 0.05) and were comparable  for manual segmentation of the EC images. The SEGMENTATION module of the software was used to segment EC images. The segmented structures included the tumour, normal oesophagus, pericardium, aorta, bronchi and lung tissue, creating labels for a total of seven structures. For the outlining of each tumour region, EC contours were drawn around the total tumour volume, and any pixels <−50 HU were excluded to avoid interference with the outlining of the tumour boundary from the surrounding adjacent air, fat, blood vessels , and bone. When there was uncertainty concerning the tumour area, imaging physician's judgement prevailed.2.4Once image segmentation is complete, the original and segmented images were saved separately in “.am” format. 3D models were reconstructed using the Generate Surface in Amira software, which allows a 3D model of EC to be viewed in all directions, moved, scaled and rotated. Three‐dimensional reconstruction and visualisation can directly display the tumour's location, 3D shape and spatial relationship. Based on the 3D model, we can calculate morphological parameters of the tumour, which can help doctors identify different T stages of tumour more accurately.2.5In the 3D EC reconstruction models, the surface area volume module in Amira software was used to measure the surface area and volume of the tumour and surrounding normal tissue and to analyse the volume relationships between tumour and total oesophageal at different T‐stages. The tumour‐related lengths were measured on the 3D model using Measure: line. The measurements included the EC surface area, volume, major axis , minor axis , longitudinal length, normal oesophageal surface area, volume and longitudinal length. To exclude the influence of chance on the results, four sections were randomly selected for measurement of the major and minor axis of the oesophageal tumour and normal oesophagus. Tumour roughness and contact with the aorta were assessed based on the reconstructed 3D model and coronal, sagittal and axial CTA images.2.62.6.1https://www.ibm.com/cn‐zh/spss) for relevant statistics. Basic information surrounding cases was expressed using means ± standard deviation, one‐way ANOVA was used for comparison between multiple groups, and for independent samples t‐test was used for analysis between two groups; differences were considered statistically significant at p < 0.05.The above measurement and assessment results were analysed using SPSS software  as the horizontal coordinate (X‐axis) and the true positive rate (sensitivity) as the vertical coordinate (Y‐axis).2.6.3We invited two radiologists (the first with 5 years and the second with 10 years of experience) to independently re‐evaluate the data and their results were compared with the measure based on 3D‐model predictions, using ROC curves and AUCs to evaluate.33.1A total of 155 patients with EC were enrolled in this study, and their characteristics are detailed in Tables p < 0.05), with a strong correspondence. The proportion of neurovascular invasion gradually increased with elevating T‐stage of EC, with 22.9% in T2, 26.9% in T3 and 66.7% in T4, where it can be seen that the proportion is gradually increasing. The ulcerative type accounted for the majority (61.3%), followed by the medullary type (33.5%), mainly in the T3 and T4 stages of EC; the pathological types of advanced EC were mainly ulcerative and medullary; the roughness of EC increased with the T stage of EC, and the roughness of T4 stage EC, with a score of 3 accounting for 75%. The relationship between tumour and aorta can be used to evaluate the risk level of surgery; we found that the score of the relationship between tumour and aorta in T1 was mainly 1 (71.4%), indicating a low‐risk level at surgery; the score of the relationship between tumour and aorta in T2 and T3 was 1–2, with a higher risk level at surgery than in T1; and the score of T4 was mainly 3 (62.5%), indicating greater risk. Clinical staging was judged according to TNM stage, the clinical stage of T1 was mainly (88.9%) andII(11.1%), the clinical stage of T2 and T3 was mainly concentrated in II, III and IV, the proportion of II was 68.6% and 58.1%, the proportion of III and IV in T4 was 86.7% and 13.3%. Hence, with the increase of T staging, the clinical stage also increased with it, and the severity was higher  . Tumour volumes for T1–T4 were 12,934.36 ± 7739.25, 23,095.27 ± 14,975.67, 37,577.98 ± 36,085.64, and 58,579.25 ± 41,073.96 mm3, showing an increasing relationship, in which the EC volumes of patients with EC in T1:T2, T2:T3 were statistically different ; the EC longitudinal length, roughness score and EC volume/total oesophageal volume of patients with EC; there were no statistically significant differences between the above three parameters in the T1–T4 (p > 0.05). Tumour surface area/total surface areathe of oesophagus, tumour major‐axis length/total lengththe of oesophagus, and EC relationship with the aorta in EC patients at T3–T4 were all p < 0.05  and the correlation was poor Figure .Finally, by analysing the T3 and T4 periods, we found high correlations with AUCs >0.6 for all parameters  Figure .3, with mean major axis and mean minor axis cut‐off values of 24.25, 26.28, 37.05 and 14.69, 16.91, 25.46 mm, and EC surface areas of 4008.50, 5533.50 and 10,894.50 mm2.Table 3.4We found that the model results were better overall than the radiologists' diagnoses. By comparison, radiologists predicted different T‐stages of oesophageal cancer with an AUC value of 0.630 and the accuracy of 0.760, 0.443, 0.352 and 0.167 for T1–T4 stage of EC. Our 3D model‐based measurements had an AUC value of 0.704, higher than radiologists and the accuracy of 0.673, 0.782, 0.601, 0.752 for T1–T4 stage of EC. , which agrees with Zhao et al.'s study.Our study showed that EC surface area, EC volume, mean major axis and mean minor axis were all significantly different between different EC T‐stages (p < 0.05) had greater value in predicting the T‐stage of EC; however, the length of the tumour in the longitudinal axis (p > 0.05) was not significantly different between the different stages, consistent with the findings of Zhang et al.,p < 0.05 in distinguishing different T stages, and the AUC values of the minor axis are the highest. In comparison, the minor axis has more predictive value. Simopoulos et al.In our study, we found that the mean major and minor axis of the tumour ; formal analysis (lead); methodology ; software (lead); visualization (lead); writing – original draft (lead). Xiaoqin Zhang: Methodology ; supervision ; writing – review and editing . Wei Wu: Funding acquisition ; methodology ; project administration . Jinfeng Ma: Data curation ; resources . Jincheng Chen: Data curation ; resources . Zhu Zhang: Data curation . Liqun Liu: Data curation (supporting); formal analysis (supporting). Shanshan Xu: Formal analysis (supporting). Ximei Cao: Writing – review and editing (supporting). Yi Wu: Conceptualization ; funding acquisition ; methodology ; supervision ; writing – review and editing (lead). Huilin Cui: Funding acquisition ; writing – review and editing .This study has received funding by the National Natural Science Foundation of China (31971113), the Chongqing Science and Technology Talent Project (CQYC201905037), University Funded Science and Technology Innovation Capacity Improvement Project (2019XYY14), Chongqing Scientific and Health Committee Joint Research Key Project (2022ZDXM018), Basic Research (Free Exploration) Project of Shanxi Province (2021011079‐2) and Chongqing Excellence Package Project .The authors have no conflict of interest.The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Army Military Medical University (No. (B)KY2021165). Informed consent was objectively unavailable for this study, and subjects' privacy and personally identifiable information were protected.


To the Editor:The authors regret that there was error in the text. This notice corrects the grant number in funding information.Content of correction:Present corrected the text in the one grant number of funding information.This research was supported by the Government-wide R&D Fund Project for Infectious Disease Research (GFID), Republic of Korea (grant No. HG18C00880).This research was supported by the Government-wide R&D Fund Project for Infectious Disease Research (GFID), Republic of Korea (grant No. HG18C0088). (Revised)https://doi.org/10.4178/epih.e2022011DOI of original article


SMPD1)]-ceramide pathway. ASMase knockout (ASMase−/−) and wild-type (WT) mice bearing fibrosarcoma (MCA/129 tumour line) were treated with 10 Gy or 20 Gy in five fractions alongside or independently of USMB treatments. The results indicated that tumour responses to fractionated radiotherapy (fXRT) were enhanced when fXRT was coupled with USMB as part of the treatment regimen. Sphingosine-1-phosphate (S1P)-treated mice and ASMase−/− mice demonstrated radioresistance against fXRT alone, whereas only ASMase−/− mice showed radioresistance against fXRT treatment alone and when combined with USMB. Results indicated that in WT and S1P-treated cohorts, the use of USMB with fXRT enhanced the tumour response compared to use of USMB or fXRT alone. Although in WT and S1P-treated cohorts, there was enhanced vascular disruption, ASMase−/− cohorts demonstrated no significant vascular disruption, indicating the importance of ASMase in facilitating vascular changes in response to fXRT and USMB treatment.Recent studies have indicated that radiotherapy affects tumour vasculature as well as tumour cells. The use of ultrasound-stimulated microbubbles (USMB) can potentially enhance the effects of radiotherapy through the activation of the acid sphingomyelinase [ASMase or sphingomyelin phosphodiesterase 1 ( Summary: A novel technique using ultrasound-stimulated microbubbles coupled with fractionated radiation enhanced vascular disruption in the tumour microenvironment via an ASMase-dependent mechanism. Ionizing radiation has been used in the clinic to treat a multitude of diseases and most prominently for cancer treatment . ModeratTaking advantage of this process, radiation treatments (XRT) are often coupled with other cancer treatments, such as chemotherapy or surgery as an adjuvant or neo-adjuvant treatment. Although large curative doses of radiation (>20 Gy) are extremely effective at eliminating cancer cells, delivery of high doses of radiation comes with risks as surrounding tissue and organ damage can be inflicted through the course of the treatment. Thus, current clinical practices deliver cytotoxic radiation doses (>40 Gy) over the course of several weeks in smaller fractions (1.8-3.0 Gy) to reduce the toxic effects on healthy tissue while simultaneously invoking a curative effect against tumour cells . Even wiThe conventional theory of radiation-induced cell death establishes the action of ionizing radiation on tumour cells as the primary mechanisms that result in overall tumour control . StudiesSMPD1) is not released, leading to insignificant vascular response until total cumulative doses go beyond the minimum threshold (−/−) genotype were shown to exhibit radioresistant phenotypes in which endothelial vasculature was preserved, despite cytotoxic doses of radiation to which these tumours were exposed. Additionally, mice treated with sphingosine-1-phosphate (S1P), a ceramide inhibitor, demonstrated similar outcomes , when used in combination with XRT, can augment the effects of a single high dose of radiation . MicrobuPD is a non-invasive imaging modality that is used to measure blood flow based on the reflection of ultrasound waves off moving red blood cells and utilizes the principles of the Doppler effect to measure velocity . Current−/− mice implanted with fibrosarcoma xenografts. A group of WT mice receiving the ASMase-ceramide pathway inhibitor S1P was also included. Furthermore, this study aimed to identify the mechanism by which this combined treatment acts in the tumour microenvironment to facilitate the enhanced cell death and vascular damage. Here, we used histological analysis to examine tumour cell death and vascular disruption 72 h after treatment. In addition, PD analysis was used to complement the histology findings by determining the perfusion changes within tumours pre- and post treatment.In this study, we investigated the involvement of the ASMase-ceramide pathway in facilitating tumour vascular disruption following USMB and fXRT in C57BL/6 (black 6) mice. Experiments were conducted with wild-type (WT) and ASMase2) . Histological analysis revealed a significant decrease in detected blood vessels in WT tumours receiving radiation of 20 Gy as fractionated doses (‘F’) over 5 days  (25.5±2.3 MVD) (P<0.05) compared to that of the untreated cohort (54.3±15.3 MVD)  by counting the number of stained vessels within five to ten fields of view under a 10× objective lens (number of vessels per 0.385 mm5.3 MVD) A. HoweveP<0.05). This enhanced effect was not detected when the 20 Gy/5F treatment was coupled with USMB, but instead MVD levels were maintained (23.0±5.50), suggesting that 20 Gy/5F is capable of inflicting a maximal vascular damage effect that cannot be further enhanced  compared to that of untreated cohorts (54.3±15.3). When combined with USMB, there was a visible decrease in the number of vessels in the 10 Gy/5F group (25.6±3.0 MVD) compared to that for fXRT alone (43.5±8.0 MVD) and a significant drop compared to that of the untreated cohort (enhanced B.P<0.05) cohorts compared to the 0 Gy treatment , 10 Gy/5F (43.3±3.5 MVD) and 20 Gy/5F (39.6±7.2 MVD) groups. However, when combined with USMB, the respective fXRT treatments produced a decrease in MVD. USMB-fXRT treatment in the presence of S1P appeared to overcome the protective effect of S1P and induced a loss in MVD to a similar effect across both the 10 Gy/5F+USMB (23.2±4.7 MVD) and 20 Gy/5F+USMB  and 20 Gy/5F  groups. The combination of 10 Gy/5F with USMB (21.0±5.6%) showed elevated levels of caspase-3 staining compared to that of 10 Gy/5F treatment alone (13.4±2.5%), with staining levels comparable to those of 20 Gy/5F alone (18.4±2.3%). The 0 Gy, USMB-only (14.4±3.2%) and 10 Gy/5F-alone cohorts showed similar levels of caspase-3 staining  showed no significant elevations of caspase-3 staining detected compared to that of untreated (9.72±1.71%) and USMB-only (8.86±2.95%) tumours, indicating a protective effect C. HoweveP<0.01) (Ki-67 immunohistochemistry was used to ascertain the levels of active cell division within tumours A. fXRT aP<0.01) B.The addition of S1P appeared to have a different effect on cell proliferation in an XRT-dose-dependent manner. Tumours that underwent fXRT, USMB treatment or a combination treatment showed significantly lower levels of proliferation across all cohorts compared to those of untreated controls (44.8±4.8%). Treatment with USMB only (23.4±6.8%), 10 Gy/5F (20.1±4.1%) and 10 Gy/5F+ USMB (23.8±10.4%) showed reduced proliferation rates at similar levels, whereas 20 Gy/5F treatment (13.3±3.0%) showed further reduced proliferation and 20 Gy/5F+USMB treatment (8.8±1.2%) showed the greatest reduction in proliferation, indicating that S1P, fXRT and USMB treatment have compounding effects on tumour proliferation in a dose-dependent manner C.−/− cohorts showed no significant changes in response to treatments , with the exception of the 20 Gy/5F group showing a decrease in proliferation rates compared to those of the 0 Gy (P<0.002) and 20 Gy/5F+USMB (P<0.05) cohorts   measures the percentage change of signal detected pre- and post treatment of the tumours A. In WT P>0.05) B.−/− mice revealed overall decreases of PD signal post treatment under all conditions; however, none of these changes were statistically significantly different (Groups treated with S1P showed a trend of decreasing blood flow upon treatment with USMB. The 0 Gy (64.3±64.9), 10 Gy/5F (4.83±34.5) and 20 Gy/5F (25.1±19.1) groups showed an increase of blood flow post treatment, whereas USMB-only (−52.9±18.2), 10 Gy/5F+USMB (–54.7±22.3) and 20 Gy/5F+USMB (–54.1±14.7) treatments showed decreases of vascular signal post treatment. However, only the 20 Gy/5F treatment regimen showed statistically significant difference compared to the USMB-only, 10 Gy/5F+USMB and 20 Gy/5F groups C. Comparifferent D.Overall, PD signals collected were of very low magnitudes; thus, percentage change calculations could potentially exaggerate large levels of change found within tumour volumes. Taken together with the results being non-significant after statistical analysis, the conclusions drawn from these data can only be speculative at best.3) and day 3 for the 20 Gy/5F+USMB cohorts (0.90±0.24 cm3). Many of these mice continued to maintain or showed reduction in tumour size over the course of the subsequent days, with no rebound in tumour growth post treatment. Tumours that underwent 20 Gy/5F (P<0.05) and 20 Gy/5F+USMB (P<0.05) treatments showed significantly greater growth suppression compared to controls, whereas USMB treatment alone showed no significant differences. Furthermore, the combination treatments showed a significantly higher level of tumour growth suppression than that of fXRT alone (P<0.0001). Tumours that were not treated or treated with USMB only continued to rapidly increase in volume, tripling in size by the end of the second week, with peak tumour volume at day 9 for untreated cohorts (3.31±0.77 cm3) and at day 13 for USMB-only groups (3.39±0.74 cm3). It was also noted that most of the tumours in the 0 Gy or USMB cohorts reached the end-point size at an earlier time than tumours that were treated with fXRT or the combination treatment, and the mice were sacrificed before the end of the 29-day observation period  and day 5 for the 20 Gy/5F+USMB group (1.42±0.49 cm3) compared to controls (P<0.001). These contrasting results were seen in both the untreated and USMB-only cohorts, both of which showed continuous tumour growth with peak tumour volumes at day 19 for the 0 Gy group (2.51±0.75 cm3) and day 9 for the USMB-only group (2.96±0.50 cm3)  B.−/− genotype showed similar tumour volumes across all treatment cohorts , with tumour growth being halted and having relatively minor levels of regression over several days. Untreated cohorts (0 Gy), however, continued to grow at a rapid pace, nearly tripling in size by day 9 (3.98±0.30 cm3), resulting in early termination of all mice in accordance with research ethics guidelines  or tumour burden began to cause distress and pain were sacrificed prematurely in accordance with ethical guidelines. Individual tumour growth curves can be seen in Overall, fXRT+USMB treatments appear to suppress tumour growth, resulting in stabilization post treatment with no apparent rebounding of tumour growth within 29 days.SMPD1. The results of this study show that USMB treatment can be an effective radioenhancer in combination with fXRT and is capable of exhibiting greater tumour control compared to fXRT or USMB treatment alone. WT, S1P-treated and ASMase−/− mice were treated with either 0 Gy, 10 Gy or 20 Gy in five fractions daily with or without USMB. USMB treatments were delivered twice a week on day 1 and 5 of the fractionation schedule with a 3% microbubble tail-vein injection stimulated by a 750 kPa pressure ultrasound field. Previous studies by Kolesnick and colleagues showed that exposing fibrosarcoma (MCA/129) and melanoma (B16F1) solid tumours to single doses of 20 Gy induced high levels of endothelial cell apoptosis in WT mice, whereas ASMase−/− showed a radioresistant phenotype and reduced endothelial apoptosis  are not high enough to induce a strong cell-killing effect as cell death signalling can be inhibited by the activation of the oxygen-sensitive hypoxia-inducible factor 1 (HIF-1) complex . HIF-1 m−/− cohorts suggest a similar phenomenon in which fXRT and/or USMB treatments enhance tumour cell death despite the apparent preservation of the tumour vasculature. As such, despite the basis of the study revolving around the theory that vascular disruption drives local tumour control, it cannot be ruled out that the enhancement effect could be a result of direct or indirect influences of fXRT+USMB to tumour cell interactions or, at the very least, acts independently of the ASMase-ceramide pathway in a fractionated radiation regimen. Further studies could be conducted to definitively confirm the driving mechanism for treatment enhancement.One possible explanation for this seemingly contradictory result is that the enhanced cell death effect can occur in an ASMase-independent fashion when USMB treatment is combined with fXRT. In previous studies by Another potential explanation of the discrepancy between MVD preservation and increased cell death could be the vascular theory of radiation tumour cure. Given that the complete knockout of ASMase prevents endothelial cells from undergoing apoptosis even after taking damage from the treatments, dysfunctional endothelial cells would still remain but be unable to carry out normal endothelial function. This could lead to a reduction in perfusion within the tumour as the vascular architecture becomes compromised. Perfusion decreases as a result of USMB microvascular damage, and this has been noted to cause tumour cell death, despite the presence of endothelial cells . One imp−/− animals demonstrated very little perfusion within tumours to begin with and, as such, it was difficult to detect major changes within the tumour between treatments. Histological findings revealed that the majority of the preserved vasculature within the tumours had vessel diameters ranging from 5 to 15 μm, suggesting that ASMase−/− tumour vascular architecture consists primarily of capillary networks. This is in contrast to findings by Additionally, PD analysis demonstrated that perfusion changes in tumours can be detected when WT tumours are treated with radiation and additional treatment with USMB can cause reduced perfusion levels within tumours. Tumours treated with 10 Gy/5F showed a lower level of blood flow when treated with USMB compared to fXRT alone, indicating that there is an effect in reducing perfusion within tumours. This corresponds with the histology findings in which vasculature loss contributes to reduced perfusion. Similarly, tumours treated with 20 Gy/5F showed a decrease in perfusion compared to that in tumours treated with 10 Gy/5F+USMB, but the addition of USMB did not enhance the perfusion loss. This is reflective in the state of the vasculature as seen in the histology. In S1P-treated mice, we observed a similar effect in that perfusion levels remained similar among the 0 Gy, 10 Gy/5F and 20 Gy/5F treatments, but the combination of USMB showed a drop of perfusion, reflective of histological findings. However, results obtained from ASMaseDespite the promising results that support the hypothesis that USMB can be used alongside fXRT to enhance tumour control, this model system has several limitations. It does not take into account the impact that the immune system has on the efficacy of this combination treatment. Cyclosporine A is a well-established immunosuppressant and has been characterized in exhibiting toxicity . Althoug−/− cohorts, despite the preservation of the tumour vasculature, suggests that radiation-induced tumour cell death in fractionated regimens could be driven in an ASMase-independent fashion.In summary, the findings presented here show the importance of the ASMase-ceramide pathway in facilitating the combined effects of low-dose fXRT and USMB on the tumour microenvironment. Having previously identified that XRT+USMB treatments in single doses are capable of enhancing tumour cell-killing effects up to 72 h after treatment , the res−1 glucose, L-glutamine and sodium pyruvate  and mixed with 1% penicillin/streptomycin  and 10% (v/v) characterized fetal bovine serum . Cells were incubated in an incubator at 37°C with 5% CO2 levels maintained in culture and monitored for any forms of contamination. The medium was changed every 3-4 days or when the medium decreased in pH, as indicated by colour change of the medium. Cells were split when fully confluent often at approximately 7 days post seeding using 3 ml 0.05% trypsin-EDTA  in a large culture flask. No cell cultures used for tumour inoculation were greater than passage 8. Cell counting using a haemocytometer was conducted prior to injection to ensure an accurate concentration of 3 million cells per 100 µl injection. Cell pellets were suspended in a 1 ml solution of PBS+  and further diluted in a 1:10 ratio of PBS+. Then, 10 µl of the diluted cell solution was placed on a haemocytometer and counted. Cells were proportionally calculated as per the cell counting protocol. The total cell count in a 1 ml volume was calculated as: number of cells×100×10,000, where multiplication by 100 accounts for dilution and 10,000 accounts for haemocytometer calibration.MCA/129 mouse fibrosarcoma cell lines [obtained from Dr Zvi Fuks' and Dr Richard Kolesnick's laboratories ] were used for this experiment in accordance with the Sunnybrook Research Institute's research ethics board’s approval. Cells were grown in Dulbecco's modified Eagle medium (DMEM) with 4.5 g lin vivo model producing three distinct genotypes: WT (+/+), heterozygous (+/−) and homozygous knockout (−/−)  in 0.1% saline, starting at least 48 h before the first day of cell injection to ensure sufficient immunosuppression. Cyclosporine A (150 µl) was injected subcutaneously dorsally to the mouse on a daily schedule through treatment until the day of sacrifice. Selected WT and ASMase−/− mice were used as tumour host mice for experimentation, whereas heterozygous cohorts were used as breeder mice to further generate ASMase−/− mice. All experiments complied with Sunnybrook Research Institute's (SRI) ethical guidelines involving animal welfare and were approved by the SRI Research Ethics Board.An in-house-bred ASMase-deficient C57BL/6 (black 6) mouse line was used as our ut (−/−) . Both maApproximately three million MCA/129 cells suspended in PBS were injected into the right hind leg of mice of ages ranging between 8 and 12 weeks old. Tumours were left to grow for 1 week, until they reached a diameter of 8-10 mm in length, before beginning imagining and treatment regimens.−1 S1P in a PET solution  30 min before treatment began to ensure sufficient absorption of the endogenous chemical.In addition to the WT and the knockout cohorts, an additional cohort was added consisting of WT mice pre-treated with sphingosine-1-phosphate (S1P)  to inhibit ceramide activity. WT mice were injected with 100 mg µlThe treatment timeline  lasted 5n=60).Tumour volumes were measured pre-treatment and post treatment manually using callipers capturing the estimated length, width and height. Changes in tumour volumes were calculated with the following formula:−/− genotype, or WT mice treated with S1P. Tumours were measured pre-treatment on day 1 and were subsequently measured every two days for a total of 29 days or until tumour diameter reached a dimension of >2.0 cm, while being administered cyclosporin A daily. Tumour volume was calculated by the following formula:Four treatment regimens  were used to treat mice with a WT or ASMaseMice were sacrificed early in case tumour sizes grew beyond the endpoints or showed signs of near mortality or suffering and it no longer acceptable to continue with the study in accordance to the research ethics protocol.−1. Radiation regimens were conducted every day for 5 days as fractionated doses with a Faxitron cabinet irradiator . X-rays at an energy of 160 kVp with a source-to-skin distance of 35 cm were administered to the target tumour volumes. A full-body lead shield was used to protect the mice with a 2.5 cm diameter hole to expose tumours to ionizing radiation. Mice were divided into one of three groups with different radiation regimens: 0 Gy (control), 10 Gy/5F or 20 Gy/5F, with individual dose administrations of 0 Gy, 2 Gy and 4 Gy, respectively.Immediately after ultrasound exposure, mice were treated with radiation at a rate of 200 cGy minPD data were collected on days 1 and 8, before and after treatment, respectively. The right hind legs of mice, where the tumours were inoculated, were treated with a depilatory agent to remove fur covering the tumour region. Mice were then anesthetized using 5% isoflurane delivered via a head-covering nose-cone and were placed on a warming pad to maintain body temperature. The right leg was then fully submerged in a water bath and cleaned of bubbles or debris for scanning. A Vevo 770 ultrasound machine , using a 710B probe  with a 30 MHz central frequency (15-45 MHz imaging band), 12.7 mm focal length and 55 µm resolution, was used to acquire 3D ultrasound and PD data. Once data were acquired, mice were returned to their cages, which were warmed by a heat lamp.Histological analysis involved staining excised tissue samples with one of several tissue stains to observe morphological changes and/or differences between tumour samples and treatment conditions. Immediately after sacrifice, excised samples were divided into two portions for preservation. One half was fixed in 10% formalin  for a minimum of 48 h, before being submerged in 70% ethanol until paraffinization of the sample was possible. The other half was submerged in Tissue-Tek Optimal Cutting Temperature compound  before being wrapped in foil and submerged in liquid nitrogen to flash freeze tissue samples. Frozen samples were stored at −80°C until further use was required.Formalin-fixed paraffin-embedded tumour samples were sectioned and stained by the Pathology Research Program (PRP) Laboratory at the University Health Network . All antibodies and reagents for the respective stainings were provided by the PRP Laboratory. Tumour samples were cut into 5 μm-thin slices used for different visualization of tissue structures and protein activity. Haematoxylin and Eosin staining of tissue samples was used to observe structural and morphological changes within the tumour structure. The anti-Ki-67 antibody  was used to stain cells undergoing proliferation, and was detected using the MACH 4 kit . Anti-CD31 immunohistochemistry  was used to observe vascular endothelial cells and tumours vasculature. The anti-caspase-3 antibody  was used to observe areas of tumours undergoing early stages of apoptosis. The anti-CD31 and anti-caspase-3 antibodies were detected using the ImmPRESS anti-rabbit kit . Samples were then observed under a light microscope at 10× objective magnification for CD31 and 20× for Ki-67 visualization, and under a dissection microscope at 0.8× magnification for observing whole-tumour caspase-3-stained areas.https://imagej.nih.gov/ij/) for cell counting. Ten images were captured for Ki-67 and CD31 staining at 10× and 20× magnification, respectively, across tumour samples evenly to avoid area-capture bias. For the quantification of the percentage of cell proliferation, each image was processed using ImageJ to count proliferating cells, which were stained brown with Ki-67 immunohistochemical staining, and identify total cell number within the tumours. RGB images were split into separate black-and-white channels to generate contrast between the blue staining of background cells and brown stains of stained cells. The blue channel was used for filtering contrast of converted dark pixels for processing, whereas the red channel was used for filtering contrast of converted dark pixels of background cells. After manual curation to separate individual cells, cells were automatically counted using the built-in ‘Analyze Particle’ function in ImageJ. Once the total number of stained cells and total cell number was obtained, the proliferation index was calculated with the following formula:Quantification of Ki-67 and CD31 was conducted using ImageJ (v 1.53e)  under a 10× objective lens. For each tumour sample, five to ten fields of view were acquired and the mean vessel count was used to represent the tumour sample. A single vessel was characterized by intense staining showing a vascular track including connection branches or circular stains, indicative of a cross-sectional cut.The plugin ‘Cell Counter’ was added to ImageJ to permit a more accurate manual counting of blood vessels observed through staining of CD31. MVD was measured by counting the number of CD31-stained vessels observed within a given field of view , in which areas of brown stains indicative of cell death were detected and the percentage of cell death was calculated.t-tests were conducted between different treatment groups using a P<0.05 to indicate statistical significance. For tumour growth curves, multiple two-tailed unpaired Wilcoxon t-tests were conducted to compare significant changes between treatment groups paired with corresponding days.Statistical analysis used GraphPad 8 (v9.0.0.121) to observe significance between treatment conditions. Multiple two-tailed unpaired Welch's 10.1242/dmm.049531_sup1Supplementary informationClick here for additional data file.


We derive the governing equations for the overall behaviour of linear viscoelastic composites comprising two families of elastic inclusions, subphases and/or fibres, and an incompressible Newtonian fluid interacting with the solid phases at the microscale. We assume that the distance between each of the subphases is very small in comparison to the length of the whole material . We can exploit this sharp scale separation and apply the asymptotic (periodic) homogenization method (AHM) which decouples spatial scales and leads to the derivation of the new homogenised model. It does this via upscaling the fluid–structure interaction problem that arises between the multiple elastic phases and the fluid. As we do not assume that the fluid flow is characterised by a parabolic profile, the new macroscale model, which consists of partial differential equations, is of Kelvin–Voigt viscoelastic type (rather than poroelastic). The novel model has coefficients that encode the properties of the microstructure and are to be computed by solving a single local differential fluid–structure interaction (FSI) problem where the solid and the fluid phases are all present and described by the one problem. The model reduces to the case described by Burridge and Keller (1981) when there is only one elastic phase in contact with the fluid. This model is applicable when the distance between adjacent phases is smaller than the average radius of the fluid flowing in the pores, which can be the case for various highly heterogeneous systems encountered in real-world  scenarios of interest. Materials can be described and classified in a number of ways. For example, viscous materials have a time-dependent deformation when subjected to a strain and also resist shear flow. Another example is elastic materials that will strain when a load is applied but will returned to the same unstressed state when the load is removed. Viscoelastic materials are characterised by having both an elastic and a viscous response under deformation, and therefore can be described as exhibiting time-dependent strain ,2.There are a large variety of physical settings where we have materials that exhibit a viscoelastic response. For example, in the human spine, under normal body weight, the disks get shorter with time, which means people are shorter in the evening, and lying down (removing the body weight) allows the disks to return to normal length by morning ,4. HumanThese viscoelastic systems are usually characterised by multiple physical scales of interest. They possess a fine scale structure and this is where the various solid and fluid interactions are clearly visible . This scale is considerably smaller than the length associated with the complete viscoelastic material .Viscoelastic composites have recently been addressed by a multiscale modelling approach. In ,12,13, ahomogenization techniques. Examples of such techniques are mixture theory, effective medium theory, volume averaging and asymptotic homogenization. The choice as to which method will be suitable for the system under study should be made depending on the application of the model and the information you wish to be encoded or available from the macroscale model; however, each approach has its own benefits.When addressing a multiscale system, there are a variety of approaches that can be taken to transform a fluid–structure interaction (FSI) problem into a complete macroscale governing system. These types of procedures can be categorised as The techniques including mixture theory and effective medium theory are micromechanical approaches. These are useful when it is desirable to obtain estimates of the poroelastic coefficients for particular pore geometries. These specific geometries include spherical, ellipsoidal, or penny-shaped or in the case of diluted pores. This was considered in . Volume Previously, the asymptotic homogenization method has been a popular approach to study poroelastic materials such as in ,18,19. TIn this manuscript, we apply the asymptotic homogenization method to upscale the FSI problem between two families of solid obstacles and a Newtonian fluid phase. In this case, the medium could not be considered a porous material. Both families of elastic subphases are in contact with the fluid and each other. We assume that the length scale at which the different solid phases and the fluid are clearly resolved can be compared with the distance between each of the phases which we call the microscale. We make the assumption that this scale is much smaller than the macroscale. We then carry out an upscaling on a system of equations that describe the behaviour of each phase and is closed by the continuity of stresses and displacements on the solid–solid interfaces, and the continuity of stresses and velocities on the fluid–solid interfaces. The application of the asymptotic homogenization method leads to a set of viscoelastic-type equations, which are a generalization of linear elastic composites  and thosThe novel model derived in this manuscript has coefficients that encode the properties of the microstructure and are to be computed by solving a single local differential FSI problem where the solid and the fluid phases are all present and described by the one problem. The new model has a key difference from formulations of previous viscoelastic models. That is, our model encodes multiple different elastic phases interacting with the fluid and each other, in comparison to some previous viscoelastic formulations such as  where thWe organise this paper in the following manner. N disjoint solid subphases Our problem begins with a set We can write that the domain is Before describing the equations that govern each of the domains in our structure we first wish to clarify the notation that will be used throughout this manuscript.Remark 1.We use the following for a generic field. For a scalar we use ordinary lowercase letters, e.g., v, for a vector we use boldface, e.g., (Notation)We first require a balance equation in each of the solid domains We use nd Tβ asTδ=Cδ∇uδ,δ=Cδ∇uδ,Tβ=Cβ∇uβ,hese areCpqrsδ=Cp=Cpqsrβ,Cpqrsδ=Crnd Tβ asTδ=Cδ∇uδ,δ=Cδ∇uδ,Tβ=Cβ∇uβ,p is the pressure. Since we have an incompressible fluid we requireWe also require a fluid balance equation, we can writeUsing the fluid constitutive law  in the fRemark 2.In this work, we embrace the approach of , which m(Frequency Domain)As such, assuming continuity of velocities at the interfaces, by means of Remark 2, we haveWe also have the boundary between each of the different solid phases, which we write as itten asTδnδβ=TβnWe have now introduced all the equations necessary to carry out a multiple scales analysis. We do this by first non-dimensionalising the fluid–structure interaction problem we have just formed. This is done by introducing two distinct length scales. We use this sharp scale separation and apply the asymptotic homogenization method to the non-dimensionalised FSI problem. This leads to the derivation of the effective macroscale governing equations that describe the viscoelastic material.We can now summarise the FSI problem we introduced in the previous section. We note that the fields in each of the equations here are all defined in the time domain and where the appearance of a time derivative is shown by the multiplication of the field by We can then use the constitutive relationships , 5b), a, a5b), a problem –14j), w, w(15a)∇L with the size of the whole material the macroscale). The second scale of interest we denote with d and this refers to the microscale, which we assume can be compared to the distance between each of the subphases and the fluid. In order to clearly see the distinction between the scales, we carry out a non-dimensionalisation of the system . T. TL withIt is possible to choose different scalings for the fluid velocity and these account for the effective behaviour of fluid flow in porous media ,19,38,39We are able to use , and not problem –14j),∇=For all ive laws , 5b), a, aδ=1,…,ive laws  are(19aquations –15c) gi giδ=1,…,We are now ready to introduce the asymptotic homogenization method that will upscale the non-dimensional FSI problem –20c) to to20c) td, is much smaller than the average size of the viscoelastic material which has length L. That is,We now introduce the rules and assumptions associated with the asymptotic homogenization method which are then used to obtain the macroscale model from the FSI problem –20c). W. W20c). We require a microscale spatial variable which will describe how each field varies on the microscale, that isWe have two spatial variables We require that all the fields in –20c) ar ar20c) aRemark 3.To simplify the analysis in this work, we restrict our attention to a single subset of the domain which we call the periodic cell. This periodic cell may have a variety of different subphases, each of which can have a different geometry and elastic properties, this is depicted in ising in –20c) is isφ(l) a y-periodic. By making this assumption, we can solve the microscale differential problems arising from using the asymptotic homogenization method on just a finite subset of the material. This assumption need not be made and the analysis can be carried using a less strict assumption, i.e., the local boundedness of fields. This approach, however, only allows us to determine the functional form of the macroscale equations and the model coefficients are to be obtained by solving microscale problems on the whole microstructure of the material. This makes solving the model very computationally expensive when using the local boundedness of fields approach in comparison to microscale periodicity. Some examples of this are found in ,40,41.Remark 4.It is clear that the microscale geometry can differ depending on the macroscale point considered. This dependence is in general neglected in most works. We will make the assumption that the viscoelastic material is macroscopically uniform. That is, we assume the microscale geometry does not change with macroscale variable In the case that Equation  does not(Macroscopic uniformity)Remark 5.Ω with the corresponding periodic cell which comprises two solid subphases (one from each family) and fluid, with each of the phases denoted by In the set up of the problem so far, we have considered a fluid with many embedded subphases that are interacting. For the sake of clarity, we assume that each family provides only one subphase for each periodic cell, as shown in We now apply the assumptions of the asymptotic homogenization method, i.e.,  and 24)24), to EThe constitutive equations for the fluid and solid stress tensors under these assumptions areSince all the fields can be written in terms of a power series of the type  in 26a)26a)–28c28c, we cfined as〈φ〉i:=1|ΩWe begin by equating coefficients of ϵ0 in –26j) to toϵ0 in The quations –27c) re reϵ0 coequations –28c) ha haϵ0 coeWe now similarly consider the coefficients of ϵ1 in –26j) wh whϵ1 in Then, the constitutive Equations –27c) ha ha27c) hquations –28c) ha haϵ1 givWe have from , 31c), , 31c),  and 32b32b and tDue to the continuity of elastic displacements given by , we can see from  and (30fiven by (u(0)=ua, , 36b),  and 39)39) and wSince we have condition , we can quations , 41g) a av(0) tequations  with iωuWe now can exploit the linearity of the system –41j) to to41j) tProblem –44j) is is44j) iWe must derive the macroscale balance equation. We apply the integral averages to Equations –33c) an an33c) aThe divergence theorem can be applied to the first three integrals and we can use macroscopic uniformity condition  to rearrThe continuity of stresses interface conditions, Equations –33i), c, c33i), Our balance equation comprises the zero-th order solid stress tensors. Using Equations  and 34c34c, we kWe also want to write down the zero-th order fluid stress  since weAdding , 51) an an51) anFrom  we know We are able to describe  and 58)58) as thWe now have derived the equations necessary to write the macroscale governing equations for a linear viscoelastic composite material. That is∇x·TEff=0·TEff=0,TEff=〈CaMThe new model we derive has an important difference from previous formulations of standard viscoelastic materials. Our model has the ability to incorporate multiple elastic phases all interplaying with the fluid and each other, whereas previous viscoelastic formulations of this kind, such as , only co problem –44j), t, tCa andWe now wish to understand how our macroscale model for viscoelastic composites  and 59b59b compaRemark 6.We now wish to compare the model we derived with the results of the  in the r0), from , using b(Comparison with Burridge and Keller ).We nowWe can now use this version of the fluid stress in  to obtaiThis is still the constitutive law of our model, it had just been presented in a different form. We then rewrite the macroscale model  and 59b59b asThe constitutive equation comprises the average of the stresses in both the solid domains rial. In , the conrial. In . That isand we can identify  used in . In this used in , the sugRemark 7.We now can consider each of the differences between this model and that of  for poroation in  readswe can see that the orders of red with  and 38]∇y2v and when compared with , and we (Comparison with Poroelastic Composites ).We nowEquations , 42f), , 42f),  and 42j42j appeaThese small changes in the orders of the terms lead to the formation of only one linear dissipative problem in this work with no decoupling of the phases, rather than being able to separate the problem into a fluid problem and an elastic problem as in .In this work, we have presented a system of PDEs governing the effective mechanical behaviour of viscoelastic composites. Our constitutive law takes the form of that of a Kelvin–Voigt material, where we have the effective elasticity tensor applied to the strain plus the viscosity applied to the time derivative of the strain. Our structure comprises multiple solid fibres/subphases and a fluid phase, all of which are in contact with each other. This structure is widely applicable to many real world scenarios including modelling of human bones ,4,8,9 anWe begin our analysis by formulating the quasi-static fluid–structure interaction problem describing the behaviour of two families of linear elastic inclusions/fibres interacting with an incompressible Newtonian fluid. We then have made the assumption that both the fluid and the elastic fibres/inclusions/subphases are clearly visible and distinct on the microscale, and also assumed that the macroscale represents the average size of material we are modelling. These two scales are distinct, and their ratio leads to a very small scale separation parameter. We then enforce this distinction in length scales to upscale the non-dimensionalised FSI problem via asymptotic homogenization. The new model derived in this way retains the important properties of the microstructure such as geometry and stiffness in its coefficients, which are determined via solving the presented novel periodic cell problem.The new model that we derive comprises a balance equation and constitutive law. The viscoelastic constitutive law takes exactly the form that is expected of a viscoelastic material by comprising first the elastic constitutive relationship and second the viscous part of the relation. The addition of the multiple elastic phases in our model influences the elastic part of our constitutive law which reads like that of an elastic composite.Our new model has an important distinction from formulations of previous viscoelastic models. That is, our model encodes multiple different elastic phases interplaying with each other and the fluid in comparison with some previous viscoelastic formulations where there is only one fluid and solid phase. Accounting for these additional interactions between the multiple phases can be of particular benefit to physical applications. The differences in elastic and mechanical properties between the phases are accounted for by the multiple elasticity tensors. The latter appear in the constitutive law and are accompanied by tensors accounting for the discrepancies in the elastic properties at different points in the microstructure. In this work, we propose the novel cell problem –44j) fr fr44j) fThe addition of linearised inertia and compressibility of fluid to our model would be straightforward. In this case, we would have a system similar to that found in . These aThe current model assumes that both families of elastic phases are anisotropic linear elastic materials. We could, however, extend the model to assume that these phases exhibit hyperelastic behaviour. To do this, we would use a method similar to that found in ,46,47,48There are many future directions in which this work could be developed. A first step could be to consider the cell problems using the Fourier transform method and then applying the inverse transform to obtaining a formulation in the time domain, see, e.g., ref. . This wo


Introduction: Social media is becoming increasingly ubiquitous in the professional realm. The coronavirus disease 2019 (COVID-19) pandemic accelerated the shift towards utilizing social media to network and disseminate information, especially via Twitter. Neurosurgery programs have also leveraged Twitter to inform and attract applicants.Objective: The purpose of this study is to identify factors influencing the adoption of Twitter by matched neurosurgery applicants before and during the COVID-19 pandemic.Methods: A list of matched U.S. neurosurgery residents from just before the start of the pandemic (2019-2020) to after the peak of the pandemic (2021-2022), was collated. Twitter was searched to evaluate the presence of a professional account at the time of Electronic Residency Application Service (ERAS) submission. The following demographic variables were collected: gender, medical school, and matched residency institution.p=.001). The percentage of matched neurosurgery applicants with a Twitter profile significantly increased during the pandemic  with a two-fold increase from 20.0% to 39.7% (p<.001) in U.S. applicants.Results: Over four application cycles (2019-2022), 897 matched residents were evaluated in the study. Overall, 31.1% had a Twitter account during the time of their residency application. In particular, international medical school graduates were more likely to have a Twitter platform compared to U.S. applicants (50.0% vs. 29.7%; Conclusion: Over the past four years, an increasing number of matched neurosurgery applicants have adopted a Twitter presence during application. Driven by the increasing use of social media and accelerated by the COVID-19 pandemic, Twitter has become an important tool leveraged by during the application process. Over the last few years in the setting of the coronavirus disease 2019 (COVID-19) pandemic, there has been a noticeable resurgence of the social media app Twitter, and this revival seems to be a repurposing of the application into the professional realm as a news and networking platform more than ever before. This resurgence has expanded into the medical field, where there has been a wide and unanimous increase in its usage by residency applicants and residency programs alike, which seems to correlate with the timing of a new global focus on a more remotely accessible world that surfaced during the COVID-19 pandemic [Limited in-person opportunities and virtual interviews have encouraged applicants and programs alike to adapt to using social media platforms like Twitter to form professional connections, share medical information, and broadcast personal and departmental updates ,3. CompeThis article was previously presented as a meeting virtual poster abstract at the 2021 CNS Meeting on October 16-20, 2021.Publicly available information for U.S. neurosurgery residency programs and matched applicant names from 2019 to 2022 was obtained through the Association of Neurological Surgeons (AANS) and the respective program websites of the institutions that matched residents . Applica<0.05, representing a 95% confidence interval, was considered statistically significant.Descriptive statistics, including frequencies and percentages, were used to report demographic information. A Chi-squared test of independence was performed in IBM SPSS  to determine if there were significant associations between the presence of a Twitter account and gender, medical school, presence of IMG medical education, match year, and matched institution. An additional subgroup analysis was performed to determine if there was any relationship between the presence of applicants having a Twitter account prior to ERAS submission with the timing of the COVID-19 pandemic by stratifying the data based on the demographic factors of either gender, IMG status, or home match. A p-value A total of 897 matched residents were evaluated between the years of 2019 to 2022. There were 222, 225, 231, and 219 applicants in the years 2019, 2020, 2021, and 2022, respectively. Applicants were split into groups based on whether they matched before or during the pandemic. Those who matched in 2019 and 2020 were considered to have matched pre-pandemic, since ERAS submission deadlines and conclusion of interviews occurred before March 2020. Those who matched in 2021 and 2022 were in the pandemic group.Across all years, 31.1% (n=279) of matched applicants had a Twitter account before ERAS submission. Of 897 matched applicants, 658 (73.4%) were male and 239 (26.6%) were female. A total of 837 (93.3%) applicants graduated from a U.S. medical school and 60 (6.7%) graduated from an international medical school. About one-fifth  of applicants matched at their home institution. The majority  of students matched at another institution outside of their home medical education program. Across all neurosurgery applicants over the four application years observed in the present study, 279 (31.1%) had a Twitter presence prior to ERAS. These demographics are listed in Table Across all applicants, 207 (31.5%) males and 72 (30.1%) females had a professional Twitter profile, although there was no significant difference between gender and the presence of an active account (p=.703). IMGs made up 6.7% of all matched residents, but were more likely to have a Twitter profile compared to U.S. graduates . There was no significant difference between the percentage of applicants with a Twitter profile who matched and those who did not match at their home institution . Between the pre-pandemic and pandemic groups, the percentage of matched applicants with an account nearly doubled . Only 14.9% of applicants had a Twitter in 2019, compared to 40.2% in 2022 (p<.001). These results are listed in Table Sub-group analyses were performed to compare differences in matched applicants pre-pandemic and during the pandemic while focusing on variables such as gender, country, and home program match which are shown in Table The number of male applicants with a professional Twitter profile significantly increased from 67 (20.4%) pre-pandemic to 140 (42.6%) during the pandemic (p<.001). A similar, sizeable increase was also seen in female users from 27 (22.9%) pre-pandemic to 45 (37.2%) during the pandemic (p=.016). During the pandemic, there was a statistically significant increase in the number of U.S. medical school graduates who adopted a Twitter platform . The percentage of IMGs with an account increased from 38.5% to 58.8%, but this did not account for a statistically significant increase (p=.118). The number of applicants with a Twitter account who matched at their home institution significantly increased during the pandemic . A significant increase was also seen in those who matched outside of their home institution from 20.3% of applicants with a Twitter pre-pandemic to 42.0% during the pandemic (p<.001).Over the last few years, the COVID-19 pandemic has stimulated the growth of a social media presence among residency applicants . The risThis study investigated trends in the use of Twitter by matched neurosurgery applicants before and during the pandemic. This study demonstrates that the percentage of matched neurosurgery applicants with a Twitter account rose from 21.0% to 41.1% during the pandemic, particularly U.S. graduates who seemed to adopt the trend. One potential reason for the growth of social media during a period of national isolation and mitigation of large social events could be the small size and number of neurosurgeons and neurosurgery departments compared to other medical specialties. Given that the community tends to be tight-knit due to its compact size, there is an increasing emphasis on the value of networking and being linked into the field. With the transition to remote interview seasons and the inability to interact face-to-face with residents and faculty, the real-time social media application may have served as the best substitute for in-person insight into programs.The lack of in-person evaluations through sub-internships (Sub-Is) and interviews due to the pandemic impacted an applicant’s view of an institution as well as the converse, the program’s ability to assess an applicant . NeurosuAt the same time, residency applicants across multiple disciplines have reported using social media websites to gain information about a program’s culture, stay informed about event dates, and learn about residents’ social life -14. In pAlthough individuals usually manage their own Twitter accounts, our study is limited and dependent on the accuracy of online information, which may potentially be inaccurate. This study only utilized publicly available data, which led to some missing data points that could not be found online. Additionally, factors outside of the pandemic that may have encouraged applicants to adopt Twitter during this period were not studied. Furthermore, although we only included professional Twitter accounts, the presence of an account does not equal utility. Lastly, the focus of this study is Twitter use during the COVID-19 pandemic, so this only represents data from a four-year sample.Twitter is a powerful tool because it is a free resource and allows for the instant showcasing of information and communication between users. Increased utility and awareness of social media platforms over the last few years is reflected in the increased percentage of matched neurosurgery applicants with Twitter, particularly U.S. graduates. Further prospective surveys and retrospective analyses are still needed to quantify the role of social media for program directors, matched applicants, and unmatched applicants. As COVID-19 restrictions are being lifted and neurosurgery programs are returning to in-person events, it will be interesting the monitor if programs and applicants continue to maintain and promote their Twitter presence. Future studies should also monitor this trend in other specialties where sub-internships and other in-person networking events are not as strongly emphasized. Twitter is an increasingly popular platform for neurosurgery applicants to leverage throughout the application cycle. The COVID-19 pandemic has seen an increasing number of matched neurosurgery applicants on Twitter at the time of application.


Pten and p53 tumour suppressor genes in the mammary gland, the additional knockout of the Notch1 or Notch2 genes did not alter the kinetics of tumour onset but did significantly change the relative proportions of different tumour types. This was accompanied by changes in PI3K/AKT signalling. We suggest PI3K/AKT and NOTCH signalling interact to determine mouse mammary tumour histotype.Effective personalised cancer therapy depends on an understanding of the fundamental biological differences between tumours. Such differences may include the activation or suppression of molecular pathways involved in the development and regulation of the normal cells that give rise to the cancer of interest. One such candidate pathway in mammary/breast cancer is NOTCH signalling. In a mouse model of mammary cancer, which normally develops four different histological tumour types upon knockout of the Notch1 or Notch2 alleles into an established mouse mammary tumour model. Notch1/2 deletion had no effect on tumour-specific survival; however, loss of Notch alleles resulted in a dose-dependent increase in metaplastic adenosquamous carcinomas (ASQCs). ASQCs and adenomyoepitheliomas (AMEs) also demonstrated a significant increase in AKT signalling independent of Notch status. Therefore, the NOTCH pathway is a suppressor of the ASQC phenotype, while increased PI3K/AKT signalling is associated with ASQC and AME tumours. We propose a model in which PI3K/AKT and NOTCH signalling act interact to determine mouse mammary tumour histotype.A better understanding of the mechanisms generating tumour heterogeneity will allow better targeting of current therapies, identify potential resistance mechanisms and highlight new approaches for therapy. We have previously shown that in genetically modified mouse models carrying conditional oncogenic alleles, mammary tumour histotype varies depending on the combination of alleles, the cell type to which they are targeted and, in some cases, reproductive history. This suggests that tumour heterogeneity is not a purely stochastic process; rather, differential activation of signalling pathways leads to reproducible differences in tumour histotype. We propose the NOTCH signalling pathway as one such pathway. Here, we have crossed conditional knockout  Both inter- and intra-tumour heterogeneity remain a significant challenge to effective cancer therapy. A better understanding of the fundamental mechanisms generating tumour heterogeneity will not only allow a more precise assessment of which treatments are suitable for which cancers, but also identify potential resistance mechanisms and new approaches for therapy.Brca1 p53, Brca2 p53 or Pten p53 loss-of-function models, or in a Her2/Neu gain-of-function model, can be grouped into one of four distinct histotypes: adenomyoepithelioma (AME), metaplastic adenosquamous carcinoma (ASQC), metaplastic spindle cell carcinoma (MSCC) and adenocarcinoma of no special type (AC(NST)) [We have previously demonstrated that mouse mammary tumours developing in AC(NST)) . AdenomyAC(NST)) . AdenocaAC(NST)) .β-lactoglobulin promoter-driven CRE (BlgCre)), BlgCre Pten mice developed mainly AME and ASQC tumours, whereas BlgCre Pten p53 mice also developed MSCC and AC(NST) histotypes. In contrast, the majority of tumours from BlgCre Brca1 p53 and BlgCre Brca2 p53 backgrounds were the MSCC and AC(NST) types [BlgCre activated an Erbb2/HER2 orthologue, tumour histotype varied from AC(NST) in virgin animals to ASQC in parous animals [The proportion of different tumour types in mouse models varies depending on the combination of alleles, the mammary cell layer to which their loss is targeted and, in some cases, reproductive history. In particular, when tumour formation was targeted to mammary luminal stem/progenitor cells  that, following activation by one of a number of possible ligands tethered to neighbouring cells, undergo multiple cleavage events to release the Notch intracellular domain (NICD). NICD translocates to the nucleus, where it forms part of a transcriptional activating complex . NOTCH st cancer ,12,13,14Notch1 or Notch2 alleles into our BlgCre Pten p53 GEMM line. Notch1/2 deletion had no effect on tumour-specific survival; however, loss of Notch alleles resulted in a dose-dependent increase in ASQC and AME tumour histotypes. AME and ASQC tumours also demonstrated an increase in AKT signalling independent of Notch status. We propose a model in which NOTCH signalling does not directly affect survival, but rather, PI3K/AKT and NOTCH combine to regulate cellular differentiation pathways in mammary tumours and, thus, determine tumour histotype.Here, we have crossed conditional knockout All animal procedures were carried out according to current UK Home Office regulations following local ethical committee approval by the Institute of Cancer Research and Cardiff University Animal Welfare Ethical Review Bodies and under the authority of the appropriate personal and project licenses. ARRIVE guidelines were followed. Mice were maintained on an outbred, Black 6 (C3H) background and were fed standard diet and water ad libitum.Cre transgene under the control of the Blg promoter, driving tumour development from mammary luminal stem/progenitor cells [flox/flox p53flox/floxPten model was previously described [All cohorts carried the or cells . The Pteescribed .Notch1 and Notch2 alleles were obtained from The Jackson Laboratory (www.jax.org (accessed on 25 August 2023)) and crossed into the flox/flox p53flox/floxPten background to create an initial set of flox/wt p53flox/wt Notch(1 or 2)flox/wtPten mice. In order to minimise confounding effects of the mixing of different background strains, both control cohorts with wild-type Notch alleles and cohorts heterozygous and homozygous for conditional Notch and p53 alleles were bred from this first set of crosses heterozygous for all alleles. The full details of the animals reported here are provided in Mice carrying conditional Mice were euthanised when tumours reached previously defined humane size limits. Tumours were dissected and fixed in an excess volume of 4% neutral-buffered formalin for 24 h at 4 °C, followed by paraffin embedding. When a tumour was of sufficient size and not substantially necrotic, a piece was also snap-frozen on dry ice at time of dissection and then stored at −80 °C for later RNA and protein extraction.Histopathological analysis was carried out blinded to genotype by MJS (who has over ten years’ experience using the four-histotype classification system for mouse mammary tumours) using our previously established criteria ,2,3 baseCt method normalised to β-actin and expressed as mean fold gene expression difference over comparator samples with 95% confidence intervals.For qRT-PCR analysis of gene expression, frozen tumour material was prepared using a Maxwell SimplyRNA LEV Tissue Kit for automated extraction of total RNA . Briefly, a micro-pestle was used to grind frozen tumour material, on dry ice, prior to adding homogenisation buffer containing 1-Thioglycerol and an equal volume of lysis solution, and the relevant program used for automated RNA extraction with DNase I treatment. Samples were stored at −80 °C until used for cDNA synthesis, where 1 µg of RNA per sample was converted to cDNA using a Quantitect cDNA Synthesis Kit . qPCR reactions were performed using the cDNA as described previously . Details−, CD24+/High and Sca-1−  [Normal luminal estrogen receptor (ER) negative mammary epithelial cells isolated from 10-week-old virgin female C57Bl6 mice according to our previous protocols ,15,16 wehttps://software.broadinstitute.org/morpheus/ (accessed on 25 August 2023)).Unsupervised hierarchical clustering of relative gene expression levels was carried out on Log2-transformed data using the Morpheus online tool . The solution was then passed through a 23G needle and centrifuged for 10 min at 4 °C. The supernatant was centrifuged again, collected and stored at −80 °C. Protein extracts were separated using SDS-PAGE, transferred to PVDF membranes  and immunoblotted with antibodies against total AKT , phospho-S473-AKT  or GAPDH  as the loading control. One common sample was run on every gel to provide a normalisation standard, enabling cross-comparison between experiments. Resulting immunocomplexes were detected by HRP-conjugated anti-mouse IgG or anti-rabbit IgG secondary antibodies as appropriate and enhanced chemiluminescent (ECL) reagents . Blots were exposed to film for a range of times to optimise the appearance of the bands.Bands were quantified using ImageJ. The background value for each lane was subtracted from each ban; then, the phospho- and total-AKT values were normalised to the GAPDH value. The GAPDH-normalised pAKT was then normalised to the GAPDH-normalised total AKT to give a corrected value for AKT phosphorylation, allowing for both protein loading  and different levels of AKT . These values were then normalised to the standard control on each blot to enable different gels to be compared.2 test of distribution of categorical variables. For survival curves, the logrank test was used. ANOVA tests were used in all other cases. Significance of qrtPCR results was determined from 95% confidence intervals according to [Significance of changes in distribution of tumour types was determined by a Chirding to . All staBlgCre Pten and BlgCre Pten p53 tumours had similar levels of Notch1 expression relative to normal mouse mammary luminal oestrogen receptor (ER)-negative progenitors  [BlgCre Pten and BlgCre Pten p53 tumours had significantly higher levels of Notch2 expression relative to their cell of origin    Notch1 or Notch2 alleles. Cohorts were generated such that all mice carried homozygous floxed Pten alleles, as well as the BlgCre transgene. However, different cohorts had both heterozygous and homozygous floxed p53 and Notch alleles in different combinations. Noteworthily, it proved difficult to generate homozygous conditional p53 mice from the BlgCre Pten p53 Notch1 line. The reason for this is unknown.To determine whether Notch alleles made no difference to survival on the Pten p53 background  shorter survival, irrespective of the Notch2 allele status ; the results from p53 heterozygous and homozygous mice of the same Notch allele status were pooled. Note that if an individual animal had >1 tumour that could be analysed, the phenotypes of the multiple tumours were not necessarily the same ) as previously ,2,3. Thethe same .Notch alleles resulted in a dose-dependent increase in the proportion of ASQCs . In the Notch1 cohort, this appeared to be at the expense of MSCC and AC (NST) phenotypes, whereas in the Notch2 cohort, the AME phenotype tumours were lost, while the MSCC tumours were retained  [Dtx1, Fabp7, Fbxw7, Jag1, Jag2, Hes1, Hes2, Heyl, Notch1-4 and Nrarp).Next, we assessed whether the effects of deletion of Notch wild-type tumours were scattered throughout the data set, and there was no obvious clustering of the Notch2 knockout tumours. The Notch1 knockout tumours were particularly enriched among tumours from tumour clusters IV and V, consistent with the depletion of MSCC phenotype tumours from this cohort , and we suggested that this was dependent on a ΔNp63-regulated super enhancer [Notch1 knockout and Notch2 knockout), there was no difference in levels of activated AKT (p < 0.05), and ASQC tumours had highly significantly increased (p < 0.001) levels of pAKT, consistent with the model . Therefore, active PI3K/AKT signalling is associated with the ASQC and AME phenotypes, while the NOTCH pathway is an ASQC suppressor. As both of these tumour types are associated with high expression of the basal transcription factor ΔNp63, this is consistent with previous findings that NOTCH activation cell-autonomously dictates luminal cell fate specification in mammary epithelial cells [Notch1 or Notch2 had slightly different effects on tumour phenotype  that are specific for the tumour and would not also isolate normal cells. This also meant that for the gene expression analysis, we analysed whole tumour pieces that could potentially have included non-recombined non-transformed cells  trapped within the tumour . Importantly, however, the fact that the shift in tumour phenotypes is ‘dose-dependent’, i.e., the effect becomes stronger depending on whether the genotypes are wt/wtNotch, flox/wtNotch or flox/floxNotch, is strong, although indirect, evidence that there is efficient recombination of the conditional Notch alleles in the tumour cells.We were not able to directly confirm We find that in mouse models of mammary epithelial tumour histotype heterogeneity, the NOTCH pathway is a suppressor of the ASQC histotype, while PI3K/AKT signalling enhances both AME and ASQC. We propose these pathways act through ΔNp63. With the addition of the epithelial–mesenchymal transition as a mechanism driving the formation of metaplastic spindle cell tumours, a process which may also be regulated by NOTCH2 , a model


Since it is difficult to determine whether social media content moderators have assessed particular content, it is hard to evaluate the consistency of their decisions within platforms. We study a dataset of 1,035 posts on Facebook and Twitter to investigate this question. The posts in our sample made 78 misleading claims related to the U.S. 2020 presidential election. These posts were identified by the Election Integrity Partnership, a coalition of civil society groups, and sent to the relevant platforms, where employees confirmed receipt. The platforms labeled some  of these posts as misleading. For 69% of the misleading claims, Facebook consistently labeled each post that included one of those claims—either always or never adding a label. It inconsistently labeled the remaining 31% of misleading claims. The findings for Twitter are nearly identical: 70% of the claims were labeled consistently, and 30% inconsistently. We investigated these inconsistencies and found that based on publicly available information, most of the platforms’ decisions were arbitrary. However, in about a third of the cases we found plausible reasons that could explain the inconsistent labeling, although these reasons may not be aligned with the platforms’ stated policies. Our strongest finding is that Twitter was more likely to label posts from verified users, and less likely to label identical content from non-verified users. This study demonstrates how academic–industry collaborations can provide insights into typically opaque content moderation practices. On January 6, 2021, after a mob stormed the U.S. Capitol, Facebook announced that it was blocking then U.S. President Donald Trump’s Facebook and Instagram accounts, which prevented him from posting . Given TMethodologically, it is hard to assess platform (in)consistency at scale for two reasons. First, we do not know what content is reported to or flagged by the platforms, which complicates efforts to evaluate their enforcement decisions relative to content that is not escalated for review. Second, platforms’ terms of service can impede certain types of data collection, such as scraping .labeled.We leverage a novel cross-platform dataset of 1,035 social media posts pushing 78 misleading election-related claims posted during the 2020 U.S. presidential election that were reported to Facebook or Twitter to quantify how and when platforms labeled content. Our dataset comes from the Election Integrity Partnership, a coalition of four civil society groups , that collaborated with social media platforms ahead of the 2020 election.  we found plausible explanations for the inconsistent labeling, although these reasons may not be aligned with stated policies. For example, Twitter was more likely to label posts from verified users, and less likely to label identical content from non-verified users.Social media platforms control which misleading election content is moderated and which is not. These enforcement decisions are critical to election integrity, but we lack a descriptive understanding of enforcement consistency. This paper investigates content moderation practices to identify patterns. We also demonstrate how academic–industry collaborations can provide insight into these typically opaque practices.In what follows we discuss how prior work has measured content moderation in practice, and what we know about the effect of labeling content. We then provide an overview of Facebook’s and Twitter’s relevant content guidelines ahead of the 2020 election. Next we discuss the social media post dataset, and how we measure labeling. We then look at labeling variance, according to user type and post attributes.Content moderation is one of the most important areas of platform governance: moderation decisions have implications for the freedom of speech, information access, and online participation –14. Yet What we do know about platform content moderation policies and enforcement comes from a variety of sources, including platform community guidelines, interviews with content moderators  or curretrue news stories ” to “Missing context: The same information was checked in another post by independent fact-checkers.” We do not distinguish between label types in our analysis because 1) the number of different labels used would limit our statistical power and 2) all labels appear to have been used punitively, applied only to misleading posts. We note that our data collection and analysis methods complied with the terms and conditions for the various data sources.on the Jira ticketing system. Second, the posts in our dataset are not exhaustive. Given the scale of election-related content, the Partnership did not attempt to track every instance of each narrative online. The dataset instead includes examples of the narratives. Third, we focus only on the decision to label live content. Therefore we cannot draw conclusions about the prevalence of overall content actioning, as we excluded content that a user deleted, or that a platform suspended.Our dataset has at least three limitations. First, we focus on Facebook and Twitter because we lacked sufficient posts on other platforms to conduct variance analysis. The Election Integrity Partnership dataset contained a plurality of Facebook and Twitter posts due to the existence of tooling that made it easier to find and analyze content on these platforms. Many important platforms are not included in our dataset due to unevenness in data access or because the platform did not partner with the Partnership in general, as two tweets, for example, could spread the same misleading content, but one could be far more harmful than the other. Likewise, platforms’ enforcement policies could be based on tactics or account-level information (which could be public or private), which could vary within a claim.We note that this is not a perfect test of platform consistency Next we evaluated the relationship between user and post attributes and whether the post was labeled. We used ordinary least squares models (one model for Facebook and one for Twitter) and clustered standard errors at the narrative level. We look at the relationship between several binary explanatory variables: whether the user was verified, whether the post was in English  or the ctly see .Together, these examples illustrate the degree to which Facebook and Twitter likely struggled to consistently apply their policies. Indeed, while much of the conversation around online content moderation focuses on the contours of the policies, platforms’ ability to consistently enforce those policies deserves equal scrutiny.Our findings suggest that once platforms were made aware of misleading content, they treated narratives consistently more than two-thirds of the time. Yet there were many examples of what appear to be arbitrary enforcement. It is difficult to determine what may have caused this. While we recognize the challenges associated with moderating content at scale, these inconsistencies cannot be attributed to variations in what content was flagged for moderators; in most cases, the platforms were alerted to similar posts at the same time. One possibility is that each post was sent on to individual content moderators separately, who then made different evaluations. If this is the case, it suggests the need for further moderator training, more explicit moderation guidelines, or less time pressure imposed on moderators .Additionally, it appears that Twitter was more likely to label content from public, verified individuals. We are not sure why this is the case. It is possible that user reporting—a variable we lack insight into—was higher for public figures, but we know that Twitter reviewed all tweets in our dataset, which included tweets from both verified and unverified users. It is also possible that Twitter had an internal policy that provided a lower threshold for labeling tweets from verified users due to the greater risk that their content would go viral. We believe we are justified, however, in describing these enforcement differences as “inconsistencies” as we suspect the average social media user believes that if two people post identical content, their posts should receive the same treatment.We identified many cases in which platforms treated identical or nearly identical content differently. It is not clear to us why platforms would not create a protocol to automatically treat all instances of a news URL or video in the same way.Last, more research is needed on the effects of the (often fairly generic labels) platforms applied around the U.S. election. For example, one Facebook label occasionally applied to misleading content simply said “See the latest updates on the 2020 US Election.” A Twitter label said “Learn how voting by mail is safe and secure.” Future studies should investigate whether voters perceive such messaging as an implicit critique or perhaps endorsement of the content. Platforms can enable these studies by providing researchers with access to removed and labeled content, for example through their APIs. A broader set of researchers could then investigate content moderation decisions.S1 Appendix(PDF)Click here for additional data file.


Schwannomas (neurilemomas) are encapsulated tumours made entirely of benign neoplastic Schwann cells. They are the most common tumour of peripheral nerves, but very uncommon in gynaecologic practice.The objective is to demonstrate unusual histology mimicking schwannoma in a case of leiomyoma in a woman who had a history of vaginal hysterectomy.We report a case of a 50-year-old hysterectomised patient who was referred with complaints of dull pain in the left inguinal region of the abdominal cavity during the last 3 months. The narrated surgical video article demonstrates the dissection of the left parametrium, tumour removal, colpotomy, specimen extraction, and vaginal laparoscopic suturing. Pre-operative CT-scan images of the pelvis with retroperitoneal tumour and macroscopic and histological views of the schwannoma are also provided.Full recovery of the patient after laparoscopic removal of the tumour.As a result of the surgical treatment, the patient recovered fully.Schwannoma-like leiomyomas are rare tumours. They can be extra peritoneally located, without any connection to the uterus and adnexa. They are difficult to diagnose before surgery. The laparoscopic approach is the best option for the treatment of such rare extra organic tumours. Schwannomas (neurilemomas) are encapsulated tumours made entirely of benign neoplastic Schwann cells. They are the most common tumour of peripheral nerves. Schwannoma-like leiomyoma located in the pelvic area is an extremely rare benign tumour . Since tTo get acquainted with a successful case of the surgical treatment of a retroperitoneal tumour of unknown structure confirmed as a schwannoma after histological evaluation.We present a case of a 50-year-old patient with this pathology, who was referred with complaints of dull pain in the left inguinal region of the abdominal cavity during the last 3 months.The transvaginal hysterectomy with bilateral salpingectomy was performed 3 years before clinical presentation due to symptomatic uterine leiomyoma. The surgical procedure was typical and without any findings suggesting the presence of an extrauterine tumour. The initial surgery was performed by the same surgeon (MM). The post-operative course was uneventful, and the patient didn’t attend a gynaecologist.The initial radiological diagnosis was “left ovarian mass”, which was excluded thereafter using a contrast-enhanced pelvic CT scan. Differential diagnosis included: ovarian tumour; myoma of the round ligament or parasitic myoma; foreign body after previous surgery; extraperitoneal tumour of unknown origin.The decision about surgery was discussed with the patient. There were two indications: pain and tumour of unknown origin with the possibility of malignancy.After the surgery, the histologic evaluation using standard staining with haematoxylin-eosin with magnification X 100 was performed.For better visualisation and the possibility to examine the whole abdominal area, a laparoscopic approach was utilised. Then step-by-step the left paravesical space was developed and tumour removal was performed using the classical laparoscopic technique with bipolar grasper and scissors. We used conventional instruments including bipolar forceps, scissors, and grasping forceps. We used three 5mm working trocars and one 10mm optic trocar to optimise surgery ergonomics. Three working instruments were used to help to improve dissection precision, especially in cases of unknown extraperitoneal tumours.There was no significant bleeding. The tumour was not densely adherent to any structure in the pelvic cavity, and it was quite easy to remove it without it fragmenting.The tumour was removed through a colpotomy incision. At the end of the procedure, the colpotomy was sutured laparoscopically using a purse-string suture. Polyglactin 910 2-0 thread on CT-1 needle was utilised (see video).The surgical time was 37 mins. Intraoperative blood loss was 25 ml. No early or late postoperative complications were observed. The patient didn’t receive any blood products or postoperative treatment except for nonsteroidal anti-inflammatory drugs. The patient was discharged 24 hours after the surgery. Full recovery was achieved in 7 days after the surgery.The tumour size was 8 x 4 x 4.5cm cm with a clear capsule. It was rather cystic with thick dense walls approximately 1 cm and grey in colour. The central portion was solid, cartilage-like and yellowish in colour.The histology showed the tumour was built from multidirectional bundles of spindle-shaped cells. Tumour cells had fuzzy borders, with a moderate volume of eosinophilic cytoplasm, ovoid, and elongated nuclei. Additionally, the immunohistochemical staining for desmin and h-caldesmon was implemented with a positive cytoplasmic reaction in leiomyoma cells (see video). The patient has been observed for 1 year after surgery. There were no significant complaints and no relapse on sonographic check-up a year after the surgery.The neurilemmoma-like or schwannoma-like leiomyomas of the uterine body are very rare, they are mostly diagnosed in the gastrointestinal tract. Even though it was necessary to conduct a differential diagnosis considering many variants of uterine leiomyoma, including a parasitic tumour, histological examination made it possible to clarify the diagnosis .Power morcellation has undergone scrutiny recently because of concerns that it can disseminate occult uterine sarcoma, other undiagnosed malignancies, and benign tissue. To limit uterine tissue dissemination, morcellation may be contained within a bag .Bag extraction is prudent in all cases when extraction of the whole specimen is impossible and intraabdominal morcellation is needed or in cases of the specimen’s friable structure. In our case, it was decided to remove the tumour through a colpotomy incision avoiding risks of morcellation and without the bag because of the dense elastic structure of the specimen without any clinical suspicion of malignancy and because of the size, which corresponded to the size of colpotomy incision.The risk of recurrence in this case and this type of tumour is very low, however regular annual gynaecologic check-ups are advised.In conclusion, Schwannoma-like leiomyoma can be extra peritoneally located, without any connection to the uterus and adnexa. This rare tumour is difficult to diagnose before surgery. The laparoscopic approach is the best option for the treatment of such rare extra organic tumours.https://vimeo.com/749074872/a50f9373e2


Correction to: BMC Infect Dis22, 697 (2022)10.1186/s12879-022-07684-wCorrection to: BMC Infect Dis21, 1162 (2021)10.1186/s12879-021-06876-0The original publications of these articles contained an incorrect funding note. The incorrect and correct information is listed in this correction article, the original article has been updated.IncorrectThis study was supported by Prototype Research Grant Scheme (PRGS), PR001-2020B from the Ministry of Education, Malaysia.This study was supported by Prototype Research Grant Scheme (PRGS), PR001-2020B (PRGS/2/2020/SKK09/UM/02/1) from the Ministry of Education, Malaysia.CorrectThis study was supported by Prototype Research Grant Scheme (PRGS), PR001-2020B (PRGS/2/2020/SKK09/UM/02/1) from the Ministry of Higher Education, Malaysia.This study was supported by Prototype Research Grant Scheme (PRGS), PR001-2020B (PRGS/2/2020/SKK09/UM/02/1) from the Ministry of Higher Education, Malaysia.