Excessive tumour growth results in a hypoxic environment around cancer cells, thus inducing tumour angiogenesis, which refers to the generation of new blood vessels from pre-existing vessels. This mechanism is biologically and physically complex, with various mathematical simulation models proposing to reproduce its formation. However, although temporary vessel regression is clinically known, few models succeed in reproducing this phenomenon. Here, we developed a three-dimensional simulation model encompassing both angiogenesis and tumour growth, specifically including angiopoietin. Angiopoietin regulates both adhesion and migration between vascular endothelial cells and wall cells, thus inhibiting the cell-to-cell adhesion required for angiogenesis initiation. Simulation results showed a regression, i.e. transient decrease, in the overall length of new vessels during vascular network formation. Using our model, we also evaluated the efficacy of administering the drug bevacizumab. The results highlighted differences in treatment efficacy: (1) earlier administration showed higher efficacy in inhibiting tumour growth, and (2) efficacy depended on the treatment interval even with the administration of the same dose. After thorough validation in the future, these results will contribute to the design of angiogenesis treatment protocols. In the 1970s, Folkman discovered tumour-induced angiogenesis, i.e. the sprouting of new blood vessels from existing blood vessels, on which the growth and necrosis of solid tumours depends3. Both excessive tumour cell proliferation and lack of blood vessels induce hypoxia in the tumour microenvironment4. Tumour and the cells surrounding it secret tumour angiogenesis factors (TAFs), which stimulate existing blood vessels to induce angiogenesis5. Through angiogenesis, tumours gain a new vascular network, enabling them to receive nutrition, and metastasize and infiltrate other tissues6. The tumour microenvironment, such as TAF distribution and extracellular matrix (ECM), is central to the formation of these vascular networks7. As the complicated mechanisms underpinning tumour-induced angiogenesis are affected by both physical and chemical reactions, their specific details have not yet been fully elucidated.Cancer is a leading cause of death globally, with more than 9 million deaths per year; a number which is still increasing8. It specifically binds to VEGF, inhibiting its activity and consequently suppressing angiogenesis9. Bevacizumab is usually administered in combination with other chemotherapeutic agents10. For example, in a clinical trial of patients with non-small cell lung cancer (NSCLC), overall survival (OS) increased significantly from 10.3 months with carboplatin-paclitaxel alone, to 12.3 months when used in combination with bevacizumab11. Thus, understanding of the biological relationship among tumours and their environment including VEGF is important for enhancing of therapeutic effects of bevacizumab.Bevacizumab (product name: Avastin) has been approved by the U.S. Food and Drug Administration for the treatment of metastatic colon cancer, certain lung cancers, renal cancers, ovarian cancers, and glioblastoma multiforme of the brain. Bevacizumab is a monoclonal antibody which targets vascular endothelial growth factor (VEGF), which is considered to be the most important tissue factor among TAFs that are responsible for blood vessel formation13. Proposed models were classified into three types. The first only reproduced the phenomena of angiogenesis18. Anderson et al. developed a model that integrated both continuous and discontinuous models to describe the formation of capillary sprout networks in response to chemical stimuli from solid tumours19. The second described the tumour growth phenomena23. This type of model reproduced tumour growth and invasion when nourished by surrounding angiogenesis. For example, the diffuse interface continuum model was developed to describe the dependency of the tumour shape on cell-to-cell adhesive strength24. The third integrated tumour growth and angiogenesis30. Recently, various three-dimensional models have been reported due to improvements in computing performance33. Both tumour invasion and angiogenesis were combined in a three-dimensional model to find that tumours decompose surrounding ECM, promoting both vascular network development and tumour growth34. Lei Tang et al. used an integrated model to analyse the delivery of chemotherapeutic drugs in three-dimensional space, showing that drugs are more likely to diffuse into low-pressure regions35. From these models, several angiogenesis-related factors were identified which either promote or inhibit angiogenesis in the microenvironment. However, how the identified pro- and anti-angiogenic factors and their receptors regulate angiogenesis is not well understood.Over the past few decades, mathematical simulation models of tumour angiogenesis have been extensively developed to elucidate its mechanisms or to predict cancer progression and the therapeutic effects of drugs36. Ang1 promotes endothelial–parietal cell adhesion and vascular maturation by binding to the receptor tyrosine kinase Tie-2. On the other hand, Ang2 is secreted under a hypoxic state and acts as an antagonist of the Tie-2 receptor to weaken cell–cell adhesion. These two factors regulate the stabilization and remodelling of blood vessels and capillary sprouting in the early stage of angiogenesis37. Other molecules also regulate angiogenesis such as platelet-derived growth factor (PDGF) that affects blood vessel maturation, and fibroblast growth factor (FGF) that indirectly promotes angiogenesis by stimulating blood vessel receptors (FGFR)38. The kinetics of angiogenic growth depends on the balance between these promoting and suppressing factors. Thus, the length of new vessels is not only characterized by monotonical growth but also by regression and growth39. The inhibition of VEGF receptor signalling induces regression of angiogenesis, while its regrowth has been observed after inhibition withdrawal40. These phenomena have been mathematically proven in a VEGF receptor inhibition study41. However, to the best of our knowledge, no mathematical model has reproduced the mechanism of vascular regression that occurs without drug administration.The angiopoietin family consists of four types of angiogenic factors, Ang1 to Ang4, which are expressed by vascular endothelial cells. These factors regulate adhesion between vascular wall cells and endothelial cellsThis study aimed to develop a three-dimensional simulation model integrating angiogenesis and tumour growth. Temporal vascular regression was reproduced by incorporating the regulatory function of vascular flexibility using angiopoietin. Finally, an administration simulation of the drug, bevacizumab was conducted, during which the dose and timing of drug administration were considered to maximize its therapeutic effect.35. Briefly, the model simulated the physical and chemical processes of initial tumour growth, from an un-vascularized state to a vascularized state, in three-dimensional space. The distribution of each factor, such as oxygen (O2) and TAF, was described using partial differential equations and discretised and solved numerically.In this study, we modified the mathematical model of Lei Tang et al.k point The model reproduced tumour microenvironment pressure by combining cell-induced tumour pressure (CTP) and vascular perfusion-induced tumour pressure (VTP). CTP at spatial point entclass1pt{minima2 was assumed as a necessary nutrient for tumour growth. Using Eq. . In Eq. (2] ([X] indicates the concentration of X) and [CO2] in each tumour cell. Tumour cell status classification was set as active when cell activity, The rate of Om of Eq. , was detm of Eq. .6\docume35 introduced a new concept, Cell Vital Energy (CVE), the energy stored in the cell for proliferation. This concept explained tumour cell progression to proliferation, as well as their life and death. CVE is denoted by CVE and the cell changed irreversibly to the necrotic state when CVE ≤ 0,In addition to cell activity, Lei Tang et al.35. This element of TAF is treated as a VEGF in our model because VEGF is considered to be the most principal factor of TAF8. They hypothesized that quiescent tumour cells induced by hypoxia would secrete VEGF, subsequently stimulating blood vessels and causing capillary sprouting. The VEGF concentration, c, was described using the following partial differential Eq. 37, into ing Eqs.  to 21)::37, intoThe secretion rate of angiopoietin was assumed to increase with density of endothelial cells, or TECs, in each grid point. Endothelial cell density was calculated at all grid points We described capillary sprouting and regression. In the model by Lei Tang et al., only the effect of [TAF] was considered as a promoting factor for the sprouting of new blood vessels; however, in the current study, capillary sprouting and branching were also determined via the distance of each cell from the tumour and the balance of angiopoietin concentration.mentclass2pt{minim45 When this condition was met, a new vessel could begin to sprout.Equation  reflects39. The conditions for vessels to regress were established in the same way as in Eq.  in the section “In this study, we also reproduced the mechanism of vascular regression. Vascular regression has been reported in clinical trials and is said to affect the rapid growth of neovascularizations in Eq. .25\documn of Eq. , vasculaThis section describes our model for anti-angiogenic therapy. We simulated the administration of Avastin, an anti-angiogenic drug. Avastin binds to VEGF and inhibits the sprouting of new blood vessels. We formulated the following Eqs.  and 28)28) to re3 3-dimensional space divided into 200 × 200 × 200 points on a grid. At the beginning of the simulation, five tumour cells were placed near the centre of this virtual space. Each lattice point included a maximum of one tumour cell or vascular endothelial cell.The simulation environment consisted of a 1 cm48, including the density of endothelial cells e0, the concentration of VEGF at the tumour boundary c0, and the concentration of Ang-1 a0. The boundary conditions were set as follows: n = 1, w = 0, c = 0, d = 0, As a numerical calculation, each partial differential equation was normalized and solved with Finite Difference Method. For dimensionless parameters, we employed several parameters used in the model of Jackson et al.2 and Ang1 uniformly diffused throughout the space, sufficient nutrients present, and blood vessels in a stable state. The assumptions were as follows:Tumour cells become active when cell activity, Tumour cells irreversibly change from a survival state to a necrotic state when CVE is < 0.Tumour pressure, Tumours migrate or grow toward the lower interstitial pressure of 26 neighbouring grid points.Ang2 and Ang1 are expressed in TEC and normal endothelial cells, respectively.Ang2 expression begins when an existing vessel satisfies the condition of Eq.  upon VEGMore than 3 days after new sprouts, vascular regression occurs with the probability calculated by Eq.  when theThe various parameters used in this simulation are shown in Table Initial assumptions included O2), metabolic waste (CO2), and angiopoietins, were repeatedly calculated. Movies of angiogenesis-induced vascular network formation and tumour growth, and VEGF diffusion, are available in Video We performed a tumour angiogenesis simulation for 60 days. Figure Figure 2] distribution. Initially, the whole space is green, indicating the uniform distribution of O2 in the space . Furthermore, existing vessels turned yellow , indicating that O2 was secreted and highly concentrated , confirming nutritional status deterioration inside the tumour , it was not statistically significant. Figure P = 0.0379 (Student's t-test corrected Bonferroni correction) confirming statistical significance. These results indicate an increase in new vessel length and the number of tumour cells with early and late drug administration, respectively. Figure We observed the effect of administered bevacizumab on tumour growth and angiogenesis. Initially, to estimate the most effective administration time for tumour growth inhibition, we performed Avastin-treatment experiments in three different administration periods: 30–40 days, 40–50 days, and 50–60 days, in a 60-day simulation. Figure Both final new vessel length and tumour cell numbers were found to be shorter and larger, respectively, with later bevacizumab administration. New vessel length changes in the non-drug condition indicated that length began to increase from day 35, increasing faster from 50–60 days than before day 50  confirming statistical significance. The mean and SD of vessel length at 30–50 days of drug administration was 4.69 × 102 ± 0.535 × 105 mm.We investigated optimal anti-angiogenic agent administration intervals to make treatment more effective. Figure 5 ± 0.0270 × 105. On the other hand, the highest number of tumour cells was observed when the drug was administered for 30–60 days, with a mean number of tumour cells and SD of 0.724 × 105 ± 0.207 × 105. Although administration for 30–50 days resulted in 1.53 times as many tumour cells as those observed after administration for 30–60 days, P = 0.168 , the result was not statistically significant. Figure Figure The final length of new vessels was found to decrease with increasing administration intervals. This may be due to the drug acting during the 50–60-day period, during which vascularization increased rapidly, for similar reasons as drug administration timing. Confirming the final number of tumour cells in each condition, the results indicated that they were 6.18% lower when the drug was administered for 20, rather than 10, days. This indicates that bevacizumab is more effective at inhibiting tumour growth when administered over a long period rather than an intensive short period. However, the final number of tumour cells was 53.5% higher when the drug was administered for 30 rather than 20 days.2 was supplied to the tumour during the 30–40-day period, when the drug was administered for 30–60 days, than when the drug was administered for 30–60 days, indicating that inhibition effects on vasculature growth were insufficient for tumour growth inhibition.According to the overall trend, Fig. According to this simulation, we propose that medication should be administered at a pace of no less than every other day to inhibit tumour growth. Finally, a combined comparison of all three conditions suggested that bevacizumab could most effectively inhibit tumour growth when administered with compatible duration and interval of administration.Some study limitations must be acknowledged. First, parameters in this simulation were adopted from several studies, rather than one, which may affect the results of this study. Second, vessels and tumours were fixed to each grid point and could not change their shape in response to the surrounding environment. Third, as this study focused predominately on sprouting vessel status changes, we did not consider tumour invasion or metastasis. Hence, we implemented only VEGF as one of the TAFs that promote angiogenesis while other molecules also function. Additionally, our results must be evaluated and validated in future clinical experiments and, if necessary, our model may be easily modified and updated.This study developed a three-dimensional simulation model of angiogenesis and tumour growth. Specifically, we implemented the angiopoietin concentration balance, resulting in the reproduction of angiogenesis recession during vascular network formation. Furthermore, the efficacy of bevacizumab administration was evaluated using this model. Earlier administration showed higher tumour growth inhibition efficacy, with efficacy dependent on treatment interval even when the same dose was used. Following rigorous validation in the future, these results will contribute to the design of angiogenesis treatment protocols.Supplementary Information.Supplementary Video S1.Supplementary Video S2.


P = 0.175). The specificity of GMS was 81.82%, which was higher than that of PAS . The negative predictive value (NPV) for PAS and GMS were 53.33% and 75.00%, respectively. The positive predictive value (PPV) for PAS and GMS were 91.18% and 94.59%, respectively. This study showed that special staining of LCT in BAL fluid may be a novel method for the diagnosis of IPA, and the GMS of LCT had higher sensitivity and specificity, which was superior to PAS.In recent years, various biomarkers have been gradually applied on bronchoalveolar lavage (BAL) fluid for the diagnosis of invasive pulmonary aspergillosis (IPA). The objective of this study is to assess the value of the liquid-based cytopathology test (LCT) for improving the identification of IPA in BAL fluid from possible IPA patients, following special staining with periodic acid-Schiff staining (PAS) or Grocott's methenamine silver (GMS). A total of 47 consecutive possible IPA patients who underwent bronchoscopy with BAL fluid from January 2017 to December 2018 were included. 45 people had a pair of BAL fluid specimens and 2 patients had two BAL fluid specimens. The 49 pairs of BAL fluid specimens were processed for culture, tuberculosis acid fast staining smear, direct microbial smear, and LCT with special staining (PAS and GMS), respectively. Then, we compared the sensitivity and specificity of PAS and GMS in BAL fluid in high-risk patients. Among 47 possible IPA patients, 25 patients had proven/probable IPA, and 11 patients had other invasive fungal diseases. The sensitivity of GMS was higher than that of PAS (92.11% versus 81.58%;  Pneumocystis jirovecii and Aspergillus spp. are frequent. Microbiological diagnosis of P. jirovecii infection is commonly based on microscopic detection of cysts and trophic forms . Sim. Sim4]. (87.88%)  17]. Me. MeMucorAs mentioned above, special staining of LCT-prepared slides in BAL fluid have many advantages in the process of IPA diagnosis. The slices prepared by LCT and staining are automatically prepared, thus avoiding the interference of practitioner factors. Liquid-based cytology of bronchial aspiration and bronchial brushing materials can even be prepared into cell blocks for the diagnosis of more diseases and molecular tests . HoweverIn our research, our pathologists have some experience in microbiology detection after long-term training and communicate with the respiratory department and microbiology room in time. However, pathologists in other places have not mastered the knowledge of microbiology morphology, so we hope that this technique will be further promoted, and pathologists will communicate with the respiratory department and the microbiology room, which will improve pathologists' ability to diagnose microorganisms under the microscope.As a whole, our study shows that LCT-based special staining in BAL fluid seems to be a novel method for the diagnosis of IPA, and the GMS of LCT is superior to PAS, which has higher sensitivity and specificity.


British Journal of Cancer provide in vivo evidence that the degree to which various breast cancer cell lines acidify their environment correlates with their ability to metastasise to the lungs. This indicates that measurements of tumour extracellular acidosis have the potential to become a clinical tool for assessing the risk of metastasis.Solid tumours are often highly acidic compared to normal tissue, and tumour extracellular acidosis contributes to multiple aspects of cancer progression. Now, Anemone et al. in this issue of the  More precisely, however, this excessive extracellular acid stems from the combined contributions of both H+ from glycolysis and acid in the form of CO2 from oxidative metabolism, which are extruded from the cancer cells and accumulate in the torturous, insufficiently vascularised tumour interstitial space.3 Despite their elevated metabolic acid production, the intracellular pH (pHi) of cancer cells growing at an acidic extracellular pH (pHe) is less acidic than that of normal cells under similar conditions, because the cancer cells greatly increase their capacity for acid extrusion.4 Importantly, this not only helps them survive the potentially toxic acidosis, but can endow cancer cells with additional advantages, including chemotherapy resistance, immune evasion, and increased invasiveness and metastasis.6 Collectively, this strongly suggests that the ability of cancer cells to acidify their environment is related to their aggressiveness, rendering precise tumour pHe measurements highly clinically relevant. However, most methods for in vivo pH imaging are either of relatively low resolution, lack the ability to distinguish pHe and pHi or are not safe for clinical use. These include microelectrodes, which are invasive and imprecise, positron emission tomography approaches, which report on a composite of pHe and pHi, and genetically encoded or injectable optical imaging techniques, which are often not clinically relevant and remain limited by the lack of sufficiently specific near-infrared pHe probes.2It has been known for decades that the tumour microenvironment is acidic.British Journal of Cancer, Anemone et al.7 used magnetic resonance imaging (MRI)-based, pH-sensitive chemical exchange saturation transfer (MRI-CEST)9 to demonstrate that extracellular acidosis correlates with tumour metastatic behaviour in vivo. Employing spontaneous BALB-neuT mammary tumours as well as syngeneic engrafting of metastatic and non-metastatic mammary cancer cell lines in BALB/c mice, they created spatial pHe maps of primary tumours and defined an acidity score highlighting pHe heterogeneity. They found tumour pHe to be profoundly acidic, below 6.8 in the most aggressive models, and less acidic but still below pH 7, in the less aggressive tumour models. Supporting earlier reports,11 they demonstrated substantial heterogeneity of tumour pHe. The acidity score, albeit not the average tumour pHe, correlated significantly with the number of lung metastases. This appeared to at least partly reflect cancer cell-autonomous properties, as invasiveness also correlated inversely with pHe in vitro.In this issue of the 13 the work by Anemone et al.7 takes this an important step further by combining the precision and clinical potential — MRI-CEST has been used in patients— of MRI-CEST with studies of mammary cancer phenotype. Notably, they found that the tumour acidity score correlated not only with metastasis, but also with the expression of cancer stem cell markers in the tumour tissue, extending earlier reports that stemness in glioma models is dependent on an acidic niche pHe.15 To further interrogate the relation between pHe and metastatic capacity, Anemone et al. used a complementary approach: they adapted 4T1 cells to growth at chronic acidosis and showed that, although the primary tumours formed by the acid-adapted cells grew more slowly than their normal pH counterparts, they acidified the tumour microenvironment more, and, concomitantly, gave rise to an increased number of lung metastases. Interestingly, in this case, this was not recapitulated in vitro, where the acid-adapted cells were less invasive than wild-type cells. This demonstrates that for reasons that are still elusive, the correlation between acidosis and invasive/metastatic behaviour is context-dependent and apparently stronger in vivo than in vitro.While earlier studies have proposed a correlation between invasiveness and extracellular acidity in tumours,7 and other6 studies are clearly indicative of some degree of causality. However, it must be stressed that pHe impacts pHi, and that acidic pHi is growth inhibitory, even for cancer cells.4 Thus, it seems likely that additional factors, such as effects of pH on anti-cancer immune response and vascularisation,4 may contribute in the in vivo setting, and we are still far from a full understanding of the complex pro- and anti-tumorigenic effects of acidic tumour pHe. It would therefore probably be naive to think that simply making tumours less acidic overall will be a magic bullet for reducing metastatic potential. Indeed, studies in which tumour pHe was increased by oral HCO3− administration have shown opposing effects on metastasis in different models.17 Curiously, HCO3− treatment failed to significantly alter tumour pHe in the model used by Anemone et al., and if anything, slightly increased the number of lung metastases. Another approach would be to directly target net acid extruding transporters. Supporting the therapeutic potential of this, such transporters are frequently upregulated in cancer cells, and their inhibition or knockdown has been shown to reduce primary tumour growth18 as well as in vitro invasion.19The most pertinent open question in the study is that of causality. In other words, to what extent does the correlation between extracellular acidity and metastatic potential reflect a driver role for extracellular acidosis per se, and to what extent does it simply happen because cancer cells with very high metabolic acid production and a corresponding need for net acid extrusion are also the most aggressive ones? Acidosis is clearly favourable for extracellular matrix degradation, and observations such as the metastatic behaviour of acid-adapted cells observed in thise and other hallmarks of the tumour microenvironment in regulating metastatic behaviour. For instance, microenvironmental hypoxia and acidosis can exist both independently and in an overlapping manner in tumours,11 yet the impact of varying combinations of these factors is essentially unstudied. MRI-CEST can already be combined with other clinical imaging modalities,8 and, for instance, combined pH- and hypoxia mapping in tumours could be a highly informative tool, both in basic research and translated to a clinical setting. As such, the study by Anemone et al. is an early step, but an important one. While the sample studied is yet too small to provide evidence of a global correlation, let alone causality, between pHe and metastasis, it clearly shows that clinically relevant mapping of tumour pHe with high spatial resolution has the potential to predict cancer aggressiveness. This opens for the possibility that tumour pHe imaging could once become a valuable tool for predicting metastatic potential in a clinical setting.Another key open question is the relation between acidic pH


Orthopoxvirus/MPX-positive sample and at least one VZV-positive sample within the same disease event. Between September 2009 and April 2014, 134 of the 1,107 (12.1%) suspected MPX cases were confirmed as MPX/VZV coinfections. Coinfections were more likely to report symptoms than VZV-alone cases and less likely than MPX-alone cases. Significantly higher lesion counts were observed for coinfection cases than for VZV-alone but less than MPX-alone cases. Discernible differences in symptom and rash severity were detected for coinfection cases compared with those with MPX or VZV alone. Findings indicate infection with both MPX and VZV could modulate infection severity. Collection of multiple lesion samples allows for the opportunity to detect coinfections. As this program continues, it will be important to continue these procedures to assess variations in the proportion of coinfected cases over time.Recent enhanced monkeypox (MPX) surveillance in the Democratic Republic of Congo, where MPX is endemic, has uncovered multiple cases of MPX and varicella zoster virus (VZV) coinfections. The purpose of this study was to verify if coinfections occur and to characterize the clinical nature of these cases. Clinical, epidemiological, and laboratory results were used to investigate MPX/VZV coinfections. A coinfection was defined as a patient with at least one  Orthopoxvirus (OPXV) in West and Central Africa. Most of the human infections reported each year are from the Congo Basin of the Democratic Republic of Congo (DRC). Monkeypox (MPX) disease presentation, including the characteristic rash, most closely resembles that of smallpox, an eradicated disease caused by a closely related OPXV. Monkeypox disease presentation is often confused with another febrile rash illness, varicella zoster virus (VZV). Previous evaluations of MPX laboratory-based surveillance have noted a large number of VZV infections among cases that were MPX negative, often in the same area where MPX cases occurred.4Monkeypox virus (MPXV) is an endemic 5 Monkeypox patients often experience a febrile prodrome with high fever 1–4 days before rash onset, whereas a low-grade fever at rash onset is more common for VZV. Lymphadenopathy is also a distinguishing MPX characteristic. Lesions on the palms of the hands and soles of the feet are often noted in MPX patients; although this feature is not recognized as a significant VZV characteristic, it has also been noted in VZV patients.6 Monkeypox lesions are firm, deep-seated, well-circumscribed with a central point of umbilication; present at a single stage of development on any one site of the body ; and evolve slowly with each stage, lasting 1–2 days.8 Varicella zoster virus lesions are usually more superficial in appearance with irregular borders, can be present at multiple stages on any one site on the body, and rapidly evolve from macules to crusts within 24 hours. Varicella zoster virus infection results in lifelong latent infection of the dorsal root ganglia, and reactivation with a dermatomally distributed painful rash illness (zoster) is common, particularly in persons older than 60 years.9Clinical diagnosis of MPX based on rash examination during the early macule and papule stages can be challenging. Key differences between MPX and VZV disease presentation at symptom onset and during illness progression can help to establish a presumptive diagnosis.11 Varicella zoster virus does not have an animal reservoir and is characterized by widespread human-to-human transmission. Secondary attack rates for VZV among susceptible household contacts were estimated at 87%.12 In temperate climates, primary infection of VZV generally occurs in early childhood. By contrast, primary infection of VZV in tropical regions often occurs in adolescents and adults.14 Seroprevalence rates for VZV are understudied in Africa, and few studies of VZV seroprevalence have been conducted in MPX-endemic countries. In Ghana, 45% (54 of 120) of healthy participants aged 16–46 years were seropositive for VZV.15 A serosurvey of children aged 6–59 months in the DRC showed a VZV seroprevalence of 8%.16 Patients with MPXV and VZV coinfections have been previously noted in the DRC.19Epidemiological patterns also differ between MPX and VZV. Monkeypox is a zoonotic disease with relatively limited human-to-human transmission.We describe the detection of both MPXV and VZV in persons investigated for suspected MPX infection via an enhanced MPX surveillance program in Tshuapa Province, DRC. The unexpectedly large number of detected coinfections was examined for biological plausibility. The purpose of this study was to confirm that MPX and VZV coinfections do occur and to characterize the clinical nature of these cases. Case demographics, symptom, and clinical severity, including rash burden, are described and evaluated in comparison to individuals with MPX or VZV infection alone. Temporal and locality trends of coinfection cases were investigated to determine if coinfections are present at a rate greater than would be expected by chance alone. The findings of this analysis will have implications for MPX disease surveillance and case management in the DRC.Human MPX is a mandatory reportable disease in the DRC. An MPX case definition was implemented in October 2010 for enhanced surveillance in Tshuapa Province. A suspected case was defined as follows: a patient with a vesicular pustular eruption characterized by hard and deep pustules and with at least one of the following symptoms: fever preceding the eruption, lymphadenopathy , and/or pustules or crusts on the palms of the hands or soles of the feet. A formal investigation of a suspected MPX case included the collection of samples and the completion of a case investigation form by a trained surveillance officer. Surveillance officers are provided with sample collection kits that contain two swabs , two sterile tube  for crust collection, two tools to unroof crusts , and an MPX-specific case investigation form. Surveillance officers are trained to collect a sample from two different lesions, for a total of at least two samples for each case. Lesion swabs and/or lesion crusts are the preferred samples for MPX diagnostics. Blood samples were rarely, but sometimes, collected.These activities were determined to not be research by a CDC human subjects advisor.20 In the absence of OPX DNA amplification, a second real-time PCR assay for VZV-specific DNA signatures was conducted . Patient samples that yielded positive findings for OPX were not tested for VZV at the INRB. Prepared DNA remainders from these samples and unprocessed additional lesion samples were shipped to the CDC Poxvirus Laboratory, Atlanta, GA.One sample type from every case was processed and tested at the Institut National de Recherche Biomédicale (INRB) in Kinshasa. The INRB tested for OPX DNA signatures using an OPX-generic real-time PCR assay.23 Including diagnostic results from both the CDC and INRB, a patient was considered a confirmed MPX case if at least one sample was either positive at the INRB (OPX-specific assay) or positive at CDC’s Poxvirus Laboratory . Independent of the laboratory results for MPX, a patient was considered a confirmed VZV case if at least one sample was positive for VZV at the CDC or INRB.The unprocessed lesion samples received at the Poxvirus Laboratory were processed, and DNA was extracted. The DNA, along with DNA previously processed at the INRB, was tested using the MPXV-specific real-time PCR and VZV-specific real-time PCR assays.2 before adding fresh medium. Flasks were observed daily for 9 days for cytopathic effect. Positive flasks were harvested when the monolayer was approximately 100% infected, or if the cell culture was older than 1 week after initial plating, and cytopathic effect was limited.Viral isolation was attempted for lesion samples that yield an MPXV real-time PCR Ct value less than 32. Viral isolation was performed in a T25 flask of African green monkey kidney cells (BSC-40). Roswell Park Memorial Institute (RPMI) 1640 media was supplemented with 2% heat-inactivated fetal bovine serum, L-glutamine, penicillin–streptomycin, amphotericin B, and gentamicin. Inocula comprising 2 mL RPMI 1640 plus 20 μL sample were incubated with the cells from 1 hour to overnight at 35.5°C and 5–6% CO24Crust samples that were dual positive at the CDC were evaluated by electron microscopy (EM). A small amount of the processed sample (crust homogenate) was mixed 1:1 with 5% paraformaldehyde and allowed to inactivate for 24 hours. Electron microscopy grids were enhanced with 1% Alcian blue and prepared using the drop-to-drop method.Based on the initial analysis and laboratory results obtained for samples collected from suspected cases, a coinfection case classification algorithm was formulated. This algorithm was subsequently applied to the full body of surveillance data available for 1,271 suspected MPX cases, investigated between September 2009 and April 2014 . A totalP-value < 0.05 was considered statistically significant. Frequencies were calculated for demographic data for each case category. Frequencies for reported signs and symptoms were calculated and stratified by case category. Time and space clustering of coinfection cases were assessed by evaluating health zone, illness onset, sample processing, and testing dates to look for associations. Comparisons of demographic characteristics and rates of signs and symptoms were made between case categories using chi-square or Fisher’s exact tests. Age was assessed as both a continuous variable (Student’s two-tailed t-test) and as a categorized variable (chi-square).All statistical analyses were computed using SAS software version 9.3 . A t-test. Cases were additionally categorized into rash burden groups established by the WHO: benign (1–25 lesions), moderate (26–100 lesions), grave (101–250 lesions), and plus grave (> 250 lesions). The distribution of rash burden groups was compared using a chi-squared test. Individuals were excluded from specific analyses when a variable of interest was missing from their case report forms.Rash burden was calculated using the sum of the reported lesion counts on each part of the patient’s body. The continuous variable for lesion count was compared between case categories using a pooled two-sample A large proportion of patients investigated between September 2009  and December 2012 were confirmed as both MPX and VZV cases based on results from independent MPX and VZV laboratory tests. Of the 427 cases (766 samples) investigated during this time, 40 (9.4%) were positive for both MPX and VZV.n = 20) of these individuals had a dual positive crust sample, 45% (n = 18) had a dual positive swab sample, and 10% (n = 4) had a dual positive blood sample  processed and tested at the INRB, with their respective DNA remainders tested at the CDC. An additional 45 lesion samples from these individuals (21 crust and 24 swab) were processed and tested at the CDC. All 40 had at least one sample that was dual positive for MPX and VZV by PCR testing at the CDC. Fifty percent . Negative stain EM was then performed on four of crust samples, two samples with and two without the noted cytopathic effect . In the A coinfection classification algorithm was created based on these findings. A patient was classified as a coinfection if 1) at least one sample was positive with OPX-generic assay or MPX-specific real-time PCR and 2) at least one lesion sample tested positive for VZV PCR testing at the CDC, or a lesion (crust) sample tested positive for VZV assay at the INRB. Varicella zoster virus-positive PCR results at the CDC from a DNA remainder crust sample were included as a confirmation for VZV when a primary lesion sample was not available for VZV testing.P = 0.7) or VZV-alone cases (mean: 18.14 years) (P = 0.07).One thousand two hundred seventy-one suspected MPX cases occurring between September 2009 and April 2014 were included in the final analysis. One thousand one hundred seven individuals had a sufficient, comprehensive set of laboratory results to be categorized using the case classification. Of these, 36.1% (400) were confirmed MPX cases, 41.3% (457) were confirmed VZV cases, 12.1% (134) were confirmed MPX/VZV coinfections, and 116 (10.6%) were negative for both MPX and VZV , Table 2In addition to rash and fever, the most frequently reported signs and symptoms of coinfection cases included fatigue (86.1%), chills (80.1%), headache (73.9%), and myalgia (67.3%). When controlling for age, coinfection cases were significantly less likely to report signs/symptoms including mouth sores, axillary lymphadenopathy, cough, sore throat, and being “bed-ridden” than MPX cases . CoinfecP-values: 0.002–0.02). There were no significant differences in the presence of lesions by body location for coinfection cases compared with VZV cases. The total lesion count for coinfections  was significantly higher than that for patients with VZV alone . When categorized into rash burden groups, coinfections were significantly more likely to be categorized into the higher rash burden categories than VZV cases  and the other zone having nine coinfections of 57 investigated (15.8%). The zone with the largest number of coinfections (39 or 22.9% of investigated) also had the highest number of VZV-only cases (102/170 [60%]).There were no discernible temporal or seasonal associations detected for coinfection cases, although the data available for these comparisons were somewhat limited. The proportion of coinfections among investigated cases remained constant month-to-month and year-to-year. There were no identified correlations between the timing of illness onset and sample processing for coinfection cases.19 this study was unique in that we were able to investigate biological plausibility of these coinfections by cell culture and EM analysis of dual positive original samples.Human MPX is a mandatory reportable disease in the DRC, and enhanced MPX surveillance was initiated in Tshuapa Province in 2010. In-depth case investigation forms allow for disease presentation and severity assessments. A unique feature available for this analysis was the collection of multiple lesion-derived samples from individual patients. In-country training has led to an increase in optimal sample type (swab/crust) collection for MPX laboratory-based diagnosis. Although previous studies have noted MPX and VZV coinfections in the DRC,19 This evaluation of samples collected from coinfection cases in this study suggests that MPX and VZV cause distinct lesions. Not any sample from one lesion has shown to have both OPX and VZV virions by EM, although only a few lesion samples have been examined.A large proportion of coinfections were unexpected at the initiation of this analysis; however, recent studies have shown similar rates of coinfections in the DRC.There were discernible differences found in the severity and reported symptoms for those with coinfections compared with those with either MPX or VZV alone. Coinfection cases were more likely to report signs/symptoms associated with MPX illness and had higher lesion burden than cases with VZV alone. However, coinfection cases were less likely to report these signs/symptoms and had an overall lower rash burden than cases with MPX alone. These findings indicate that coinfection with these two rash viruses could modulate the severity of the overall infection.25 or an unknown pathogenic factor specific to infection with one or both viruses18 has been noted as an explanation for the coincidental detection of both viruses from a single patient. However, the mechanism behind the coinfection with MPX and VZV remains indefinite. One hypothesis is that initial infection with either virus causes the patient’s immune system to be more susceptible to a secondary infection. It is also possible that VZV lesions causing breaches in the skin may serve as an ideal entry point for MPXV infection after contact with infected individuals or animals. Recent serosurveys of young children in the DRC have shown that VZV seroprevalence is very low, and the comingling of these two viruses among a wide age-group is not unexpected.16Co-circulation of both viruses,26 and MPX might be able to trigger reactivation independently of age. Moreover, the ability of infectious agents or their components to induce the reactivation of herpesviruses from latency has been documented in the literature. Historic case reports following primary smallpox vaccination indicate infection with OPXs has been shown to activate HZ.28 Identifying and obtaining samples for PCR testing from the hypothetical index HZ case could be difficult, particularly if lesions have resolved before an outbreak is investigated. However, alternative diagnostic methods such as antibody avidity could help to elucidate this hypothesis. Underlying medical conditions (such as HIV) have not been well documented in this area and might also contribute to the risk of VZV reactivation.Another possibility is that infection with MPXV directly triggers VZV reactivation resulting in herpes zoster (HZ). Shedding of VZV from an index HZ case may result in transmission of the virus to susceptible persons in the community. Most coinfected individuals in this analysis were younger than would be expected for VZV reactivation; however, HZ can occur in younger individuals,There were several limitations to this study. Education and training for enhanced surveillance in this area has dramatically improved the proportion of MPX cases among the total number of cases investigated. As a consequence, the proportion of VZV cases detected has decreased over the 4 years. The proportion of coinfection cases however has remained fairly consistent over this same time period. The lack of spatial or temporal associations for coinfections may be due to several factors. Fluctuations in the number of suspected cases investigated may be a by-product of outreach activities and weather, such as the rainy season. There may be a lag in reporting of suspected cases while surveillance officers are away from their posts, and subsequently an increase in cases once officers return for investigations. This could obscure any associations between case classifications and season/location. As enhanced surveillance continues, these short-term lags in investigations may decrease, allowing for a more robust analysis.This analysis encompasses the early part of enhanced surveillance program (2010–2014). Increases in training and improvements in distinguishing MPX cases from VZV or other rash diseases are the primary goal, making it difficult to assess changes in incidence for these two viruses over time. Comparisons between coinfection cases and VZV-alone cases are also influenced by the MPX focus of the enhanced surveillance. Therefore, these VZV cases likely do not represent the full picture of VZV illness or incidence in this area.Another limitation is the possibility for cross contamination between the multiple samples from one case. Results from this analysis indicate that coinfections have distinct MPX and VZV lesions. One possibility for crusts that were positive by PCR for both viruses but not by EM might be that multiple crusts are collected and placed into one tube, allowing for low levels of contamination that are detectable by a sensitive real-time PCR assay. Project personnel verified that independently collected crusts from a case were often placed together in a tube for transport to the laboratory. On the other hand, swabs are more likely to be collected and stored inside the individual swab sleeve, greatly reducing the chance for cross contamination. Cross contamination is unlikely to be a major factor in this study as five blood samples (four cases) were dual positive for MPX and VZV. Improving sample collection and storage procedures would allow for a better assessment of the viral makeup of individual lesions. Our sample set of double positive lesion samples was limited to make a more robust conclusion.29 Amid fears of bioterrorist deliberate release of smallpox, the CDC conducted a 2-year evaluation of a smallpox rule-out algorithm; 75% of cases suspected to be smallpox were confirmed as varicella infections.30 Since the implementation of universal childhood varicella vaccination in the United States, physicians have less experience with varicella and little experience with OPX infections and, in the context of lingering concerns about variola, may still mistake varicella for OPX disease. It will be important to pursue studies targeted at understanding mechanisms responsible for the presence of both MPX and VZV in rash illness outbreaks in Central Africa.The co-circulation of similar diseases caused by distinct infectious agents is unusual if not unprecedented. During smallpox eradication, the disease most frequently mistaken for smallpox was varicella.The collection of multiple lesion samples for this enhanced surveillance program allows for the detection of both MPX and VZV by PCR and the opportunity to detect coinfections. As this program continues, it will be important to continue these sample collection procedures to assess variations in the proportion of coinfected cases over time. In addition, an adjustment in the sample testing protocol in country may be prudent. If samples can be tested for both OPX/MPX and VZV at one time, it may help to provide a more comprehensive view of coinfection cases when combined with CDC laboratory results.Supplemental materials


Glioblastoma might have widespread effects on the neural organization and cognitive function, and even focal lesions may be associated with distributed functional alterations. However, functional changes do not necessarily follow obvious anatomical patterns and the current understanding of this interrelation is limited. In this study, we used resting-state functional magnetic resonance imaging to evaluate changes in global functional connectivity patterns in 15 patients with glioblastoma. For six patients we followed longitudinal trajectories of their functional connectome and structural tumour evolution using bi-monthly follow-up scans throughout treatment and disease progression. In all patients, unilateral tumour lesions were associated with inter-hemispherically symmetric network alterations, and functional proximity of tumour location was stronger linked to distributed network deterioration than anatomical distance. In the longitudinal subcohort of six patients, we observed patterns of network alterations with initial transient deterioration followed by recovery at first follow-up, and local network deterioration to precede structural tumour recurrence by two months. In summary, the impact of focal glioblastoma lesions on the functional connectome is global and linked to functional proximity rather than anatomical distance to tumour regions. Our findings further suggest a relevance for functional network trajectories as a possible means supporting early detection of tumour recurrence. After standard treatment, which consists of maximal safe resection followed by radio- and chemotherapy with the alkylating agent temozolomide, the vast majority of patients experiences early and abrupt tumour recurrence3. Recurring tumours are often extensive in size, more likely to involve both hemispheres, and quickly progress to terminal disease stages4. Thus, early detection and localization of tumour recurrence is key to initiate salvage treatment at an earlier stage.Glioblastoma (GBM) is one of the deadliest types of cancer with profound impact on the individual patient’s neurocognitive function and quality of life5. However, structural MRI does not appreciate the full extent of GBM as infiltrative margins are typically not visualized. Indeed, upon histology tumour cells of high proliferative potential and invasive capacities have been proven even far beyond the tumour edge within macroscopically normal brain parenchyma8. In addition to structural imaging, task-based functional MRI (fMRI) has been recognized as a relevant tool for preoperative mapping of eloquent cortical function9. However, task-based fMRI strongly depends on the patient’s compliance and ability to perform a task, which may be compromised by the brain tumour itself11. Hence, task-independent resting-state fMRI is gaining increased attention for its ability to evaluate functionally relevant areas even in impaired or non-compliant patients13. Indeed, resting-state fMRI-derived networks were found to exhibit stable characteristics within individual patients14, which renders them a promising candidate marker for longitudinal personalized evaluations.Structural contrast-enhanced magnetic resonance imaging (MRI) is the gold standard for preoperative and longitudinal tumour mapping since it is non-invasive and offers high spatial resolution15. Gliomas located in the left parietal cortex were found to be associated with widely reduced connectivity within the extended bilateral default mode network16, unilateral gliomas were found to disrupt long-range inter-hemispheric connectivity17, and restricted lesions to induce a global reconfiguration of network complexity18. Conversely, spatially distributed lesions might impact the same functional networks and produce identical neurological symptoms20. Hence, the precise spatio-temporal interplay of tumour, network alteration, and functional compensation/reorganization is just beginning to be understood22.Only recently, the global impact of brain tumours, even if circumscribed lesions, on brain networks has been acknowledged. For instance, higher alterations of the network structure were observed in high-grade as compared to low-grade gliomasIn this work, we hypothesized that network anomalies are not restricted to areas of spatial tumour involvement but distributed more globally and follow a functional rather than a spatial distance to the tumour. To answer this question, we quantified tumour-induced network anomalies of patients with GBM based on their deviation from network connectivity of a healthy control population Fig.  and diseWe assessed functional network anomaly using anomaly scores as quantitative measures. In 14 out of 15 patients, we observed highly anomalous voxels with anomaly scores less than − 2.3 preferentially distributed along their functional distance to tumour-bearing voxels rather than their spatial distance Fig. . Specifi2 = 0.94, p < 0.001), whereas a lower but still significant correlation  was found for the dorsal attention network   Fig. b.Figure As supratentorial resting state networks are also represented in the cerebellum in a crossed hemispheric way, we independently evaluated the presence of propagated network anomaly within cerebellar resting state networks and again found symmetric anomaly, even though the bi-hemispheric correlations were not as network-specific as within the cerebrum Fig. b. For boLongitudinal trajectories of the individual patient’s network anomalies revealed a recovery in form of a decrease in network anomaly at the first follow-up two months after surgery Fig. . This chFinally, we compared the timing of (re-)occurrence of network anomaly and recurrence of contrast-enhancing tumour in five patients where we had extended longitudinal data Fig. . Importa23. In our study, network anomaly refers to the relative deviation from network connectivity of a control population and does not necessarily reflect increased or decreased activity. To ensure that the observed global alteration of networks was not simply due to tumour-associated destruction and loss of axonal connections, we excluded all tumour-bearing voxels when calculating network anomaly scores. Thus, the reported changes are observed in connections not directly destroyed by the tumour. Vice versa, inclusion of all directly tumour voxel-related connections did not change the observed patterns of network anomaly, which supports our hypothesis of a global tumour impact on the entire network architecture. Even though the exact mechanisms remain speculative, such a global impact might be due to forward-propagation of locally perturbed connections within one network (such as tumour-associated destruction and oedema) to hierarchically connected further networks. Of note, the global impact we observe is in line with recent work that also included tumour-bearing voxels in their analysis15. Our results corroborate recent studies which observed a shift in connectivity profiles in patients with newly diagnosed glioma23. Especially high-grade gliomas showed increased disturbances, accompanied by altered hub-non-hub connectivity. It is also in line with the concept of GBM being a disease that involves the entire brain, which is best exemplified by its highly invasive growth capacity with single tumour cells that invade the most distant brain regions24. Indeed, a more extensive impact on neurologic function and network connectivity than merely explained by the macroscopic mass lesion has been documented for interhemispheric connections26. Here, we advance this concept of GBM as a whole brain disease by highlighting the fact that tumour-related network alterations may be spatially widely distributed as long as they are functionally close. In fact, we found functional proximity to even dominate the pattern of involved resting-state networks, while spatial distance in the anatomical space did matter to a lesser extent. This is especially true for within-network propagations to the contralateral hemisphere, which leads to a systematic and regular involvement of both cerebral hemispheres.We used resting-state fMRI to evaluate changes in the functional network structure of 15 patients with GBM at time of diagnosis and longitudinally tracked changes during treatment and follow-up in a subset of patients. We found patterns of network alterations across all patients irrespective of tumour size or location. In all cases, focal lesions were associated with widespread and symmetric anomaly in both hemispheres in a network-specific manner across all seven resting-state networks in line with recent work27. The relatively larger impact of functional tumour proximity on network anomaly was especially evident in the spatially distributed higher-order networks such as the dorsal and ventral attention networks. In contrast, spatial distance seemed more relevant in tumours that involved spatially restricted networks such as the visual, limbic, or somatomotor networks. Reassuringly, network anomalies were mirrored in the contralateral cerebellum, as previously shown for task-based brain activation29 and surgery-related alterations30. In concordance with these studies, our findings suggest that cerebellar network activity is readily altered by focal cerebral lesions, albeit not necessarily mediated through structural connectivity .Symmetric involvement is in line with a brain geometry that is defined by functional connections as a relevant alternative to an anatomical space34, and cognitive decline has been found to precede MR imaging-defined tumour recurrence35. The widespread network anomalies that we observed might hint at the neural basis of those deficits, however no neurocognitive assessment was possible in our cohort and thus the relationship remains speculative. A more detailed assessment of the individual patient’s neurocognitive function as part of the routine patient care is warranted and might also add to our current understanding of disease-related quality of life. Moreover, the striking symmetry of network anomaly was independent of right- or left-hemispheric tumours and contrasts clinically relevant lateralization of neurologic functions such as language, which suggests an important, so far neglected role also for the non-dominant hemisphere.From a clinical perspective, several studies have observed a considerable neurocognitive deterioration in patients with glioma37. Our findings corroborate previous results and first demonstrate near total or supra-total recovery of functional network activity upon GBM surgery. The short time period until recovery at first follow-up  suggests transient and reversible alterations mediated by the tumour and surgical intervention rather than true plasticity of network architecture.So far, only few studies have investigated the impact of neurosurgery on the brain’s functional network structure. Together they suggest a transient decrease in spontaneous neuronal activity in the cerebellum and reduced connectivity among default mode regions or interhemispheric connections of motor areas, all of which typically resolve within 3 months39. However, in contrast to those techniques, resting-state fMRI enables fast, cost-effective, and non-invasive prediction of tumour growth without the need for radioactive tracers and specialized imaging units. Given the exceedingly poor post-recurrence survival of patients with GBM, the ability to predict tumour growth by two months will impact the clinical scenario by bringing second surgeries and/or adjuvant treatments forward to a point in time, when the disease is still localized. This will ultimately result in a higher rate of second remissions and more individualized patient management. However, future research is necessary to determine the causes that underlie network anomaly and dissect the relative contributions of tumour infiltration, oedema/reactive changes, neurovascular uncoupling40 or other biochemical effects38.A major strength of our approach is the ability to follow individual patient’s network trajectories in parallel to structural tumour evolution beyond perioperative phases throughout the entire disease course. By doing so we observed consistent and specific network alterations at locations, where subsequent tumour recurrence became evident two months later. Even though not all regions with altered connectivity, especially remote from the original tumour site, necessarily corresponded to areas of future tumour growth, the consistency and predictive value of preceding network anomaly in four out of five patients suggests that resting-state networks are sensitive to microscopic tumour growth and/or increased oxidative demand, thereby rendering resting-state fMRI a promising marker for the early detection of tumour recurrence. Similarly, other imaging methods such as PET or magnetic resonance spectroscopy add value to the visualization of invasive margins beyond structural imagingOur study has limitations. First and most important, the sample size of our cohort is limited and continued assessments in larger patient cohorts with additional focus on longitudinal measurements will be crucial to precisely define the role of resting-state fMRI in advancing our understanding of varied neurologic/neurocognitive phenotypes of brain tumour patients, as well as translating it to routine clinical practice. In this regard, a comparison also to other brain tumour types will be helpful to better delineate characteristics unique to patients with GBM and differentiate them from other infiltrative and non-infiltrative brain tumours such as meningiomas or metastases. For the moment, we decided to focus on patients with primary glioblastoma  to ensure a homogeneous tumour behavioural background given variable tumour locations. Also, larger multicentre studies that incorporate different MR scanners and sequences will be needed to establish the analytical performance of resting-state network anomaly as a potential biomarker. Along this line, image analysis of brain tumour patients is especially challenging due to the structural lesions the tumour may cause. In particular, it might be impossible to reliably align and quantify diseased brains, which prompted us to manually inspect and adapt all pre-processing steps carefully to make sure not to introduce any errors. The network anomaly maps we created are based on functional connectivity, which per se is primarily a function of higher cortical areas. Hence, they may not reliably detect aberrations due to subcortical white matter lesions . Still, our single case-based observation is too premature to confirm or rule out a relevant association. Finally, and most importantly, future studies will benefit from addition of more detailed and time-consuming neuropsychological assessments since the observed global network anomalies suggest global neurocognitive alterations. Unfortunately, advanced neuropsychological data were not available for our initial cohort. Similarly, the restricted sample size with variable tumour locations, lesion sizes, and associated neurological symptoms prevented us from further subgroup analyses based on functional or spatial lesion overlap.In summary, we assessed network anomaly in patients with GBM and found widespread, highly symmetric network alterations that follow a functional rather than spatial proximity to the tumour and are mirrored in the cerebellum. We further show that network deterioration is ameliorated within two months after neurosurgery. Ultimately, we find network alterations to precede structural tumour recurrence by two months, which highlights the potential of resting-state network anomaly as clinically relevant marker for the early detection of GBM recurrence.5, by determining the increase in contrast-enhancing and non-enhancing FLAIR/T2W lesions, or the occurrence of any new lesions. An overview of the study cohort, primary tumour location, tumour extent and the number of longitudinal follow-up scans is given in Supplementary Table The study cohort consists of 15 consecutive patients (61.2 + /- 10.1 years) with newly diagnosed GBM, IDH wildtype, WHO grade IV to ensure a more homogeneous tumour background. Six patients were longitudinally followed using bi-monthly structural MRI and resting-state fMRI. Tumour progression was defined according to response assessment in neuro-oncology (RANO) criteria41. This dataset comprises resting-state fMRI scans of 80 healthy individuals (aged 65.3 + /- 6.2 years), acquired at the same MR scanner type , comparable EPI sequence , and resting-state condition .As a control cohort we used the University of McGill subset of a larger publicly available datasetMRI data were acquired using a Siemens TrioTim 3.0 T MRI, equipped with a 12-channel head coil, at the Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna. The MR imaging session comprised acquisition of high resolution structural images, including T1-weighted sequences  pre- and post-intravenous contrast media application (0.1 mmol/kg body weight of a gadolinium-based contrast agent), a T2-weighted sequence , and a FLAIR volume . For functional MR images an EPI sequence was employed  with a total scan time of 10 min. Patients were instructed to relax, not to fall asleep and to keep their eyes closed.42. First, the structural T1 volume was skull-stripped and segmented into grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Then, the T1 volume was nonlinearly registered to the Montreal Neurological Institute (MNI) template using deformable registration via attribute matching and mutual-saliency weighting (DRAMMS)43. DRAMMS incorporates mutual saliency weighting to account for missing correspondences or the structural impact of pathologies such as brain tumours. All normalizations were carefully checked for errors, and the acquired normalization was applied to the segmented brain tissues. The fMRI data was motion corrected, where the functional volumes were registered to the mean volume, and framewise displacement (FD) was calculated to quantify motion outliers. The fMRI data was co-registered to the anatomical T1 volume, and the transformation obtained by DRAMMS was applied to normalize the fMRI data. Denoising was performed with ICA-Aroma44 with subsequent nuisance regression including the average WM, CSF and global signal as well as their first derivatives as regressors. Additionally, high-pass filtering with 0.01 Hz was applied, and no low-pass filtering was conducted45. The fMRI volumes were resampled to 3 × 3x3 mm voxel size, and spatially smoothed with 4 mm full width half maximum (FWHM). High motion time points with a framewise displacement > 0.5 mm were censored46. A liberal grey matter mask was created based on the control cohort resulting in approximately 60,000 voxels. Voxel-wise functional connectivity was quantified with Fisher z-scored Pearson’s correlation coefficient.Data pre-processing was performed with FSL v547. The four structural image acquisitions  were used to quantify four distinct tumour tissue classes: necrotic tumour, enhancing tumour, non-enhancing tumour, and oedema. Tumour segmentations were manually inspected and corrected for segmentation errors. Additionally, resected tumour regions were manually delineated and added to the segmentation. Tumour segmentations were normalized with the transformation obtained by DRAMMS and smoothened with 3 mm FWHM to ensure a liberal tumour masking.Automated tumour segmentation was performed with Bratumia49 and calculated the row-wise cosine similarity between each individual connectivity matrix and the reference connectivity matrix using only positive correlations. We discarded negative correlation values and used only positive relations to obtain interpretable values ranging from zero (dissimilar connectivity pattern) to one (highly similar connectivity pattern). This resulted in patient-specific vectors, where each entry quantifies the voxel-wise similarity of the connectivity profiles, providing a distribution of similarity measures across the control cohort for each voxel. We then characterized this distribution by quantifying the median and the median absolute deviation (MAD), which allowed us to calculate a patient-specific voxel-wise robust measure of dispersion50.For each patient we quantified the voxel-wise similarity in connectivity patterns and its deviation from the control population Fig. a. First,anomaly score.For each patient and resting-state acquisition we calculated the similarity to the reference control connectivity matrix and projected the resulting similarities into the control baseline distribution by subtracting the median and dividing it by the MAD Fig. b. SubseqFor each patient, individual tumour voxels were excluded from the patient-specific connectivity matrices as well as for the control connectivity profiles. We calculated an individual baseline distribution for each patient, removing the affected patient-specific tumour voxels also in the control cohort. We removed voxels labelled with any of the four segmented tumour tissue types or segmented as resection. Tumour segmentations were slightly smoothed to make sure not to include any voxel directly affected by the pathology. Although anomaly maps calculated with and without tumour voxels were highly correlated  and the absolute correlation of the average connectome in controls  to all other non-tumour voxels. Precisely, for each tumour voxel we calculated Pearson’s correlation between the distances and the anomaly scores of non-tumour voxels, and quantified whether a shorter anatomical distance or a stronger functional proximity relates more to higher anomaly. We compared positive relationships between distance and anomaly for functional proximity and spatial distance respectively. Voxels were excluded from comparison in case no positive correlation was observed and labelled as “no positive relationship”. Of note, to exclude effects driven by impaired connections to tumour-bearing regions, connectivity values between tumour and non-tumour voxels did not enter the calculation of the anomaly maps. For each patient, we calculated the percentage of tumour voxels to which highly anomalous voxels (z-score < − 2.3) rather follow a spatial or a functional distance.We analysed whether aberrant connectivity patterns followed a spatial distance or a functional proximity to the tumour. For each patient and tumour voxel (labelled as enhancing or necrotic tumour tissue) we quantified the Euclidean distance  to characterize the fit.To explore the relationship between network anomaly score and structural tumour evolution, we evaluated the coincidence of future tumour regions and anomaly scores at the acquisition time-point before enhancing tumour progression or recurrence was apparent upon structural imaging. One patient (Patient 06) had to be excluded from further analysis since it was not feasible to precisely quantify enhancing tumour tissue at time of follow-up scan due to motion artefacts during the contrast-enhanced T1-weighted image acquisition.52 or post-surgical effects. Between two consecutive follow-up scans t0 and t1, we quantified the enhancing and necrotic tumour present at time-point t1 but not at time-point t0. Subsequently, we compared the network anomaly scores between these prospectively emerging tumour voxels and all other voxels in the tumour vicinity with a two-sample permutation test. To exclude any bias introduced by segmentation errors, we analysed only follow-up scans where at least 3 cm3 were labelled as new enhancing tumour at time-point t1.We compared the anomaly scores of future tumour regions to anomaly scores of voxels which were spatially within a 1 cm margin to the previous tumour or resection cavity, which we refer to as “tumour vicinity”. Tumour vicinity provides a more appropriate baseline for comparison than the overall average brain due to potential tumour infiltration53 to restrict the proportion of false positive findings to 5% (q = 0.05).All statistical tests were based on permutation-based testing, appropriately corrected for multiple comparisons using the false discovery rate (FDR) procedureSupplementary information.


The accurate description of the behavior of fluids in nanoporous materials is of great importance for numerous industrial applications. Recently, a new approach was reported to calculate the pressure of nanoconfined fluids. In this approach, two different pressures are defined to take into account the smallness of the system: the so-called differential and the integral pressures. Here, the effect of several factors contributing to the confinement of fluids in nanopores are investigated using the definitions of the differential and integral pressures. Monte Carlo (MC) simulations are performed in a variation of the Gibbs ensemble to study the effect of the pore geometry, fluid-wall interactions, and differential pressure of the bulk fluid phase. It is shown that the differential and integral pressure are different for small pores and become equal as the pore size increases. The ratio of the driving forces for mass transport in the bulk and in the confined fluid is also studied. It is found that, for small pore sizes (i.e., < The widespread application of nanoporous materials in several fields, such as chromatography, membrane separation, catalysis, etc., has lead to a growing interest in the accurate description of the thermodynamic behavior of fluids confined in nanopores ,3,4,5,6.P, and the integral pressure V, the two pressures are related by [Recently, Galteland et al.  reportedlated by ,20:1)P simulations of LJ fluids. The simulations are carried out in a modified Gibbs ensemble, using two simulation boxes in equilibrium with each other. One box represents the bulk fluid, while the other simulation box represents the nanoconfined system, including walls that interact with the fluid particles, as shown in P, and temperature, T, in Simulation Box 1 are imposed, while the volume, R, and by the distance between the two parallel planes, T are imposed, while the number of particles P only for macroscopic systems Uflur. The pressure term The expression for calculating the integral pressure in Box 2 is as follows :7)p^=N2p^=N2(7)pfollows [p^fluid−fe fluid [p^fluid−wfollows [p^fluid−fquation Q=C∑The final expression in Equation  is essenIn this work, the difference between the differential and integral pressure, P, and the ensemble average of the integral pressure, B, where A and B are constants. The coefficient of determination of the fitted lines is above 0.99 showing that the relation between the A in the fitted lines) of the cylindrical pore compared to the slit pore. It can also be observed that by increasing the interaction strength between the wall of Box 2 and the fluid, In Based on the work of Galteland et al. , the sloP, of Box 1 results in a smaller change in the integral pressure, R increases, P, results in a larger difference in the integral pressure, In P, and the other a slit or cylindrical pore with repulsive or attractive wall interaction potential. In case of the attractive wall potentials, several scenarios are considered for the strength of the interaction between the wall and the fluid particles. The effect of confinement is investigated for three differential pressures, R→∞. It is shown that the increase in the interaction strength between the wall and the fluid particles has smaller effect on the difference in the pressures, R increases, In this study, the new approach reported by Galteland et al.  is used d et al. , the dif


Feedback control shows the potential to deliver efficient and personalized dose of viral injections to achieve tumour regression better than the ones obtained by former protocols. The control strategy has been evaluated in silico with parameters that represent five nude mice from a previous experimental work. Together, our findings suggest theoretical and practical benefits by applying control theory to oncolytic virus therapy.Oncolytic virus therapy aims to eradicate tumours using viruses which only infect and destroy targeted tumour cells. It is urgent to improve understanding and outcomes of this promising cancer treatment because oncolytic virus therapy could provide sensible solutions for many patients with cancer. Recently, mathematical modelling of oncolytic virus therapy was used to study different treatment protocols for treating breast cancer cells with genetically engineered adenoviruses. Indeed, it is currently challenging to elucidate the number, the schedule, and the dosage of viral injections to achieve tumour regression at a desired level and within a desired time frame. Here, we apply control theory to this model to advance the analysis of oncolytic virus therapy. The control analysis of the model suggests that at least three viral injections are required to control and reduce the tumour from any initial size to a therapeutic target. In addition, we present an impulsive control strategy with an integral action and a state feedback control which achieves tumour regression for different schedule of injections. When oncolytic virus therapy is evaluated  Oncolin vivo ,4,5. OncOncolytic virus therapy is a promising cancer therapy for various reasons. One of its main advantages is that oncolytic viruses can be engineered to target specific tumour cells without damaging healthy cells ,4–6. Difin vivo [Important advances on oncolytic virus therapy were made using mathematical modelling of within-host dynamics of oncolytic viruses in animal studies –14. Mathin vivo ,11,12,14in vivo ,14 have reachability condition has been used to formulate dynamical conditions for the containment of HIV infection by the CD8+ T cell response and antiretroviral drugs [These challenges motivate the application of control theory to improve understanding and outcomes of oncolytic virus therapy. Control theory is a mature discipline in the study of uncertain and nonlinear dynamical processes –17. Inteal drugs –23. Furtal drugs ,24,25. Aal drugs ,27. The al drugs . Thus, iin silico tested and compared with the experimental protocol used in [In this paper, we build on previous work by performing a control analysis of the calibrated mathematical model of oncolytic virus therapy developed in ,14. This used in  for five2.10 viral particles injected at days 0, 2 and 4.We conducted our analysis in the context of the experimental studies in  where geξ is composed by the number of susceptible tumour cells, S, the number of tumour infected cells, I and the number of virus particles (log10), V, i.e. ξ = (SIV)′. The output of the model corresponds to the total number of tumour cells T = S + I, and it is measured every 2 days. The parameters of the model are obtained from the best-fit of the model  is the state before the impulse action, and u at times To our knowledge, there is currently no analytical framework to design efficient oncolytic virus therapy. Therefore, we investigated a control scheme corresponding to oncolytic virus therapy; see the appendix. Since the oncolytic virus is injected in the body at different days , the injConsequently, we investigated an impulsive control strategy for oncolytic virus therapy; see the appendix. To that aim, we considered the model  as an im3.3.It is currently challenging to formulate efficient oncolytic virus therapy ,6,14. Th3.4.Next, we aimed to allow oncolytic virus therapy to benefit from feedback control to sustain tumour regression. We investigated the outcomes of personalized therapies with respect to changes in the frequency of injections. We used the feedback control strategy in Additionally, since different time constraints on tumour regression may apply for different patients, we investigated the impact of changes in the timings of tumour regression in each subject. We used the personalized therapy with one injection every 2 days as nominal response in each subject, and we compared the outcomes of tumour regression with a slower and faster time to enter the therapeutic zone. When the time to enter the therapeutic zone increases, the individual doses and the viral loads tend to be low at the beginning of therapy; see 3.5.in vivo despite difference in the time course of viral injections; see Since changes in the time course of viral injections could be beneficial to satisfy some preferences or constraints, we investigated whether similar tumour regression could be obtained by therapies which share similar total dose but differ in their time course of injections. We considered a schedule of one injection every two days and we compared the following two therapies which have similar total doses: (i) the time course of viral injections is dictated by the feedback control strategy which tunes the dosages of viral injections; and (ii) the time course of viral injections is dictated by an alternative protocol which changes the dosages in a staircase manner to facilitate therapy in practice; see Methods. Both therapies deliver very similar tumour regression in all subjects; the total number of tumour cells enter the therapeutic zone at the same time; see We also assessed the outcomes of common dosages for viral injections for all subjects. We compared personalized therapies with fast tumour regression to a common low dosage and a common high dosage. The common low dosage is the personalized therapy of subject 1 with the total dose of 105. The common high dosage is the personalized therapy of subject 4 with the total dose of 498. Tumour regression differs widely among subjects, suggesting that both dosages do not overcome variations in biological rates between subjects; see 3.6.r, β, dv or α have greater impacts on behaviour of the system than variations in L, and dI; see r, β, dv and α are the most influential on the output T. Since the sign of sensitivity function Sξ,p is positive for the parameters r and dv , this predicts that the parameters r and dv have a direct effect on the number of tumour cells; see β and α have an indirect effect because Sξ,β and Sξ,α are negative; see r, β, dv or α are likely to disturb the ability of the proposed feedback control strategy to achieve tumour regression during oncolytic virus therapy.Since variations in biological rates may impair the outcomes of oncolytic virus therapy, we investigated whether tumour regression is robust to some variations in biological rates when oncolytic virus therapy is performed using the proposed feedback control strategy. We conducted a sensitivity analysis to identify parameters which mainly influence the behaviour of the system ; see Metβ and α, and greater variations than the nominal value in parameter dv , a slower response of the control system is observed. This leads to higher levels of tumour cells. In these situations, given the feedback of the system the amount of virus to be injected tends to increase, but the control action results are slower than the one of the nominal situation, and therefore so is the elimination of tumour cells. Collectively, these results suggest that the proposed feedback control strategy allows tumour regression during oncolytic virus therapy to exhibit some robustness to uncertainty in biological rates. Accurate estimation of the biological rates remains essential for better efficiency.Based on these results, parametric variations are applied on these four parameters to evaluate the performance of the controller and the impact on tumour regression. We tested variations up to 4.Our findings build on previous studies of oncolytic virus therapy by applying control theory to deliver new insights and efficient protocols. A number of experimental studies have been conducted to test the concept of oncolytic virus therapy ,6. Thesein vivo. These insights would be useful to inform the design of virus therapies and control strategies to ensure tumour regression with low toxicity.In this study, toxicity was not included as a constraint in the design of the controller and in the subsequent dosages of viral injections. The toxicity tests in ,32 showeSince the dose at a given day tends to increase when the time between injections increases, safe high-dose injections could be delivered to grant injection-free periods to patients and clinicians. The results here presented suggest that the outcomes of therapy mainly depend on the total amount of injected virus rather than the scheduling and time course of viral injections. This feature provides flexibility in the design of protocols. Thus, protocols could be adjusted to satisfy different preferences and constraints such as the number of follow visits, the posology of viral injections, or toxicity.A given dosage of viral injection may perform differently in different subjects due to difference between the biological rates of each subject. Some subjects exhibit a beneficial property because the total dose and frequency of viral injections decrease up to some extent without compromising treatment outcomes. When biological rates are known, personalized protocols could be formulated to take advantage of patient-specific dynamics to improve the outcomes of therapy. When biological rates are uncertain, it is sensible to design therapies with robust control strategies to achieve desired outcomes despite uncertainties.in vivo and the eventual high cost of viral injections. The results presented suggest trade-offs between the time to reach the therapeutic zone, the maximum tumour size expected during therapy, the viral loads in vivo, and available doses of viral injections. These findings are consistent with the ones in [When high doses are injected at the beginning of the therapy in any subject, this reduces the peak of the total number of tumour cells and the total doses. However, this scenario raises concerns about toxicity due to increased viral loads  ones in ,14.u(i) = uss, for i > =4.By tuning the control strategy to obtain only three injections that bring the tumour cells to the target, the degrees of freedom are reduced in the design to decide the time of entry to the area and the maximum of allowed tumour cells. Therefore, there is no guarantee that all patients enter the zone at the same time. This is because there is nothing in the formulation of the feedback controller that allows to handle the behaviour of the control action, so a trial-and-error method is required. In control strategies such as model predictive control, a predetermined form of the control input could be obtained by imposing constraints such as β is crucial for the outcomes of therapy. As parameter β becomes smaller, a higher control action is required to adequately regulate tumour cells. When the actual value of β is 10% smaller than the identified value, the system reaches the target after 200 days (data not shown). This shows the importance of a good identification of parameter β.The results of the sensitivity and robustness analysis are consistent with findings in ,14. In pRobustness to parameter variations can be improved by increasing the magnitude of the control input, i.e viral doses ,25,29,30In this study, viral injections are made at discrete time. However, if a continuous supply of virus is administered to the patient, for example via the blood or the respiratory tract, oncolytic virus therapy could benefit from advanced continuous time control strategies to regulate the system in different state values and sustain tumour regression in the presence of biological uncertainty.In conclusion, this paper presents the first scheme to perform oncolytic virus therapy using impulsive control theory. Although we note caveats associated with experimental testing of the proposed protocols, these could be alleviated by including constraints related to viral doses and toxicity. Together, the analysis and results here presented contribute to knowledge on oncolytic virus therapy and open new avenues based on control theory to develop effective therapies. In future works, it is envisioned experimental trials to verify the analytical results developed here.


Meningiomas are the most common intracranial tumours in humans, constituting more than one third. They occur primarily in adults, more often in females, with a peak incidence in the sixth decade. Most meningiomas are solitary and well circumscribed, they are slow growing and compress and displace the surrounding brain tissue rather than infiltrate. Brain infiltration is, however, associated with a more aggressive phenotype with increased risk of recurrence. On the other hand, meningiomas may infiltrate the dura, venous sinuses, adjacent soft tissue, nerves and arteries without necessarily being associated with aggressive tumour biology, though at the same time, preventing complete resection with potential for tumour relapse.The cellular origin of human meningiomas is thought to be the arachnoid cap cells as they share several morphologic, immunohistochemical and ultrastructural features. Furthermore, since these arachnoid cells display a wide range of epithelial-, mesenchymal- and monocyte-like properties, meningiomas may display a variegated histology with several subtypes, providing problematic differential diagnoses.NF2 gene mutations are the most common genetic alterations in meningiomas, and with increasing aggressiveness and tumour grade, the number of abnormal genetic alterations increases. Yet, apart from mutations in BAP1, SMARC1 and TERTp, few molecular genetic events have been significantly associated with a more aggressive tumour biology. Recently, DNA methylation profiling has been shown to more accurately predict tumour recurrence and prognosis compared with WHO classification.Until recently, classification of brain tumours has been based on histopathological criteria that rely heavily on the tissue of origin. However, in the latest (2016) World Health Organization (WHO) classification, molecular parameters were introduced to define several tumour entities. Meningiomas did not undergo revision, apart from reclassification of brain infiltrative meningiomas, that were seen to be aggressive and thus considered as atypical, WHO grade II tumours. Accordingly, meningiomas are classified and graded based solely on subjectively assessed histopathological features, giving considerable interobserver and sampling bias. Despite this, there is a significant association between histology and outcome in human meningiomas, resulting in the WHO classification scheme that stratifies them into three major groups, depicted as WHO grade I (benign), II ) and III . However, given that about 20% of meningiomas with a benign histology and up to about 50% of atypical grade II meningiomas recur, the current WHO 2016 classification system for meningiomas is not optimal. In order to improve prognostication and diagnostics of these tumours, novel biomarkers are required. Various groups of biomarkers have been proposed, such as proliferation markers, notably Ki-67/MIB-1. However, these biomarkers have been shown to be encumbered with interlaboratory variation and considerable overlap between malignancy groups. Similarly, growth factor receptors have also been examined without demonstrable clinical significance. Concerning molecular genetics, losses of 22q and Based on factors such as tumour size, location and histological grade, some meningiomas can result in considerable patient morbidity and mortality. Gross total surgical resection is the primary treatment. Varying rates of recurrence and progression may require repeated surgery and even radiotherapy, but all these treatment modalities are associated with various complications and adverse events. Actually, data for the best follow-up and treatment are rather weak. Related to the wide range of clinical behaviour among WHO grade I and II meningiomas, there is an urgent need to discover novel protein biomarkers and mutations that can better stratify meningioma patients for optimal surgical intervention and follow-up. Thus, one may hope that this Special Issue will shed light on various aspects of meningioma biology in our effort to improve the clinical management of these tumours.