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Sustained vaginal administration of antibiotics or probiotics has been proposed to improve treatment efficacy for bacterial vaginosis. 3D printing has shown promise for development of systems for local agent delivery. In contrast to oral ingestion, agent release kinetics can be fine-tuned by the 3D printing of specialized scaffold designs tailored for particular treatments while enhancing dosage effectiveness via localized sustained release. It has been challenging to establish scaffold properties as a function of fabrication parameters to obtain sustained release. In particular, the relationships between scaffold curing conditions, compressive strength, and drug release kinetics remain poorly understood. This study evaluates 3D printed scaffold formulation and feasibility to sustain the release of metronidazole, a commonly used antibiotic for BV. Cylindrical silicone scaffolds were printed and cured using three different conditions relevant to potential future incorporation of temperature-sensitive labile biologics. Compressive strength and drug release were monitored for 14d in simulated vaginal fluid to assess long-term effects of fabrication conditions on mechanical integrity and release kinetics. Scaffolds were mechanically evaluated to determine compressive and tensile strength, and elastic modulus. Release profiles were fitted to previous kinetic models to differentiate potential release mechanisms. The Higuchi, Korsmeyer-Peppas, and Peppas-Sahlin models best described the release, indicating similarity to release from insoluble or polymeric matrices. This study shows the feasibility of 3D printed silicone scaffolds to provide sustained metronidazole release over 14d, with compressive strength and drug release kinetics tuned by the fabrication parameters.

Glioblastoma (GBM) is a highly invasive, aggressive brain cancer that carries a median survival of 15 months and is resistant to standard therapeutics. Recent studies have demonstrated that intratumoral heterogeneity plays a critical role in promoting resistance by mediating tumor adaptation through microenvironmental cues. GBM can be separated into two distinct regions—a core and a rim, which are thought to drive specific aspects of tumor evolution. These differences in tumor progression are regulated by the diverse biomolecular and biophysical signals in these regions, but the acellular biophysical characteristics remain poorly described. This study investigates the mechanical and ultrastructural characteristics of the tumor extracellular matrix (ECM) in patient-matched GBM core and rim tissues. Seven patient-matched tumor core and rim samples and one non-neoplastic control were analyzed using atomic force microscopy, scanning electron microscopy, and immunofluorescence imaging to quantify mechanical, ultrastructural, and ECM composition changes. The results reveal significant differences in biophysical parameters between GBM core, rim, and non-neoplastic tissues. The GBM core is stiffer, denser, and is rich in ECM proteins hyaluronic acid and tenascin-C when compared to tumor rim and non-neoplastic tissues. These alterations are intimately related and have prognostic effect with stiff, dense tissue correlating with longer progression-free survival. These findings reveal new insights into the spatial heterogeneity of biophysical parameters in the GBM tumor microenvironment and identify a set of characteristics that may correlate with patient prognosis. In the long term, these characteristics may aid in the development of strategies to combat therapeutic resistance.

Background: Glioblastoma (GBM) tumors are rich in tumor-associated microglia/macrophages. Changes associated with treatment in this specific cell population are poorly understood. Therefore, we studied changes in gene expression of tumor-associated microglia/macrophages (Iba1+) cells in de novo versus recurrent GBMs. Methods: NanoString GeoMx® Digital Spatial Transcriptomic Profiling of microglia/macrophages (Iba1+) and glial cells (Gfap+) cells identified on tumor sections was performed on paired de novo and recurrent samples obtained from three IDH-wildtype GBM patients. The impact of differentially expressed genes on patient survival was evaluated using publicly available data. Results: Unsupervised analyses of the NanoString GeoMx® Digital Spatial Profiling data revealed clustering based on the transcriptomic data from Iba1+ and Gfap+ cells. As expected, conventional differential gene expression and enrichment analyses revealed upregulation of immune-function-related genes in Iba1+ cells compared to Gfap+ cells. A focused differential gene expression analysis revealed upregulation of phagocytosis and fatty acid/lipid metabolism genes in Iba1+ cells in recurrent GBM samples compared to de novo GBM samples. Importantly, of these genes, the lipid metabolism gene PLD3 consistently correlated with survival in multiple different publicly available datasets. Conclusion: Tumor-associated microglia/macrophages in recurrent GBM overexpress genes involved in fatty acid/lipid metabolism. Further investigation is needed to fully delineate the role of PLD phospholipases in GBM progression.

Abstract The rapid expansion of cancer immunology and immunotherapy builds upon the success of early immune checkpoint inhibitors (ICI) and chimeric antigen receptor T cells for some cancer types. Many gaps still exist, however, in the scientific knowledge of immune dysfunction in the tumour microenvironment and predicting clinical immunotherapy response to allow more cancer patients to benefit from immunotherapy. The Cancer Immunotherapy Collection within Scientific Reports describes pioneering preclinical and clinical studies addressing these concepts, representing significant insights and breakthroughs in the field.

Tong Mo,1,* Wenxian Huang,2,* Weisheng Sun,1 Yan Hu,3 Leroy Mcdonald,4 Zhanqi Hu,3 Li Chen,3 Jianxiang Liao,3 Bruce Hermann,5 Vivek Prabhakaran,4– 6 Hongwu Zeng1,6 1Department of Radiology, Shenzhen Children’s Hospital, Shenzhen, Guangdong, People’s Republic of China; 2Department of Pediatrics, Shenzhen Children’s Hospital, Shenzhen, Guangdong, People’s Republic of China; 3Department of Neurology, Shenzhen Children’s Hospital, Shenzhen, Guangdong, People’s Republic of China; 4Neurosciences Training Program, University of Wisconsin, Madison, WI, USA; 5Department of Neurology, University of Wisconsin, Madison, WI, USA; 6Department of Radiology, University of Wisconsin, Madison, WI, USA*These authors contributed equally to this workCorrespondence: Hongwu Zeng, Shenzhen, Guangdong, People’s Republic of China, Tel +86 18938691099, Email homerzeng@126.com Vivek Prabhakaran, Department of Radiology, University of Wisconsin, Madison, WI, USA, Tel +1 608 265 5269, Email VPrabhakaran@uwhealth.orgObjective: Neuropsychological evidence revealed language impairment in children with benign epilepsy with centrotemporal spikes (BECTS). This study investigates language function using task-activated fMRI.Methods: We conducted a language task fMRI study on three groups on a 3.0T MRI scanner, including a new onset drug naïve group (NODN-BECTS, n=11, age=9.6± 1.6), an established epilepsy with medication-treated group (Med-BECTS, n=17, age=10.7± 2.2) and a healthy control group (HC, n=18, age=10.8± 1.7). We use MATLAB14 and SPM12 to pre-process and analyze the data. A one-sample t-test was used to identify task-related brain activation changes in each group, based on the general linear model (GLM). And, then two sample t-test was performed to compare different activated regions between groups. In addition, scores on the most recent Mandarin school exams were acquired to examine and contrast extra-scanner language performance.Results: Statistical results show that some language-related brain regions (such as the left superior frontal gyrus and cerebellar vermis) were additionally activated in the NODN-BECTS group compared with the HC group. Compared with NODN-BECTS and HC groups, decreased activations were found in language-related regions in the Med-BECTS group, including the left insula, superior and middle frontal gyri, and bilateral middle occipital gyri. On the Mandarin school exams, the average score for HC was 87.3± 8.2, NODN was 84.8± 7.8, and Med was 78.2± 13.2. There was a trend toward statistical significance between the Med and the HC (p = 0.074) as well as NODN (p = 0.092) groups. No statistically significant differences were found between the HC and the NODN-BECTS groups.Significance: Language task fMRI reveals additional areas of activation in new onset BECTS compared to healthy controls which may be compensatory in nature. Antiseizure medications (ASMs) and/or longer duration of BECTS additionally appears to affect language-related regions and reduce their functional ability.Keywords: benign epilepsy with centrotemporal spikes, cognition, language impairment, functional magnetic resonance imaging

Abstract Endometrial cancer (EC) is the most common malignancy of the female reproductive system. Cancer antigen 125 (CA125) is a serum tumor marker widely reported in EC patients, particularly those with poor prognostic factors such as grade 3 tumors, deep myometrial invasion, lymph node metastasis (LNM), and extra-uterine disease. This retrospective study stratifies pre-operative CA125 levels to evaluate odds ratios (OR) and relative risk (RR) between CA125 levels and the likelihood of +LNM, lymphovascular space invasion (LVSI), grade, and stage. Patient charts for women 18 years or older with a diagnosis of EC and pre-operative or within one week CA125 measurement from January 2000 to January 2015 at a regional hospital were reviewed. OR and RR were determined by unconditional maximum likelihood estimation for CA125 levels as the predictor with staging, grade, +LVSI and +LNM as outcomes. The largest increase in risk for patients having stage I/II/III disease was 52% greater (1.52-fold risk) while largest increase in risk for patients having stage III/IV disease was 67% greater (1.67-fold risk), both at CA125 ≥ 222U/ml. Patients with CA125 ≥ 122U/ml had significantly increased risk of +LNM, with maximum increase in risk of 98% (1.98-fold risk) at 222U/ml. Patients with CA125 ≥ 175U/ml had significantly increased risk of +LVSI, with maximum increase in risk of 39% (1.39-fold risk) at 222U/ml. This study shows that elevated CA125 levels correspond to increased stage, +LVSI, and +LNM in patients with EC.

Lactobacilli, play a beneficial role in the female reproductive tract (FRT), regulating pH via lactic acid metabolism to help maintain a healthy environment. Bacterial vaginosis (BV) is characterized by a dysregulated flora in which anaerobes such as Gardnerella vaginalis (Gardnerella) create a less acidic environment. Current treatment focuses on antibiotic administration, including metronidazole, clindamycin, or tinidazole; however, lack of patient compliance as wel as antibiotic resistance may contribute to 50% recurrence within a year. Recently, locally administered probiotic such as Lactobacillus crispatus (L. crispatus) have been evaluated as a prophylactic against recurrence. To mitigate the lack of patient compliance, sustained probiotic delivery has been proposed via 3D-bioprinted delivery vehicles. Successful delivery depends on a variety of vehicle fabrication parameters influencing timing and rate of probiotic recovery; detailed evaluation of these parameters would benefit from computational modeling complementary to experimental evaluation. This study implements a novel simulation platform to evaluate sustained delivery of probiotics from 3D-bioprinted scaffolds, taking into consideration bacterial lactic acid production and associated pH changes. The results show that the timing and rate of probiotic recovery can be realistically simulated based on fabrication parameters that affect scaffold degradation and probiotic survival. Longer term, the proposed approach could help personalize localized probiotic delivery to the FRT to advance women's health.

Sustained vaginal administration of antibiotics or probiotics has been proposed to improve treatment efficacy for bacterial vaginosis. 3D printing has shown promise for development of systems for local agent delivery. In contrast to oral ingestion, agent release kinetics can be fine-tuned by the 3D printing of specialized scaffold designs tailored for particular treatments while enhancing dosage effectiveness via localized sustained release. It has been challenging to establish scaffold properties as a function of fabrication parameters to obtain sustained release. In particular, the relationships between scaffold curing conditions, compressive strength, and drug release kinetics remain poorly understood. This study evaluates 3D printed scaffold formulation and feasibility to sustain the release of metronidazole, a commonly used antibiotic for BV. Cylindrical silicone scaffolds were printed and cured using three different conditions relevant to potential future incorporation of temperature-sensitive labile biologics. Compressive strength and drug release were monitored for 14d in simulated vaginal fluid to assess long-term effects of fabrication conditions on mechanical integrity and release kinetics. Scaffolds were mechanically evaluated to determine compressive and tensile strength, and elastic modulus. Release profiles were fitted to previous kinetic models to differentiate potential release mechanisms. The Higuchi, Korsmeyer-Peppas, and Peppas-Sahlin models best described the release, indicating similarity to release from insoluble or polymeric matrices. This study shows the feasibility of 3D printed silicone scaffolds to provide sustained metronidazole release over 14d, with compressive strength and drug release kinetics tuned by the fabrication parameters.

Glioblastoma (GBM) is a highly invasive, aggressive brain cancer that carries a median survival of 15 months and is resistant to standard therapeutics. Recent studies have demonstrated that intratumoral heterogeneity plays a critical role in promoting resistance by mediating tumor adaptation through microenvironmental cues. GBM can be separated into two distinct regions—a core and a rim, which are thought to drive specific aspects of tumor evolution. These differences in tumor progression are regulated by the diverse biomolecular and biophysical signals in these regions, but the acellular biophysical characteristics remain poorly described. This study investigates the mechanical and ultrastructural characteristics of the tumor extracellular matrix (ECM) in patient-matched GBM core and rim tissues. Seven patient-matched tumor core and rim samples and one non-neoplastic control were analyzed using atomic force microscopy, scanning electron microscopy, and immunofluorescence imaging to quantify mechanical, ultrastructural, and ECM composition changes. The results reveal significant differences in biophysical parameters between GBM core, rim, and non-neoplastic tissues. The GBM core is stiffer, denser, and is rich in ECM proteins hyaluronic acid and tenascin-C when compared to tumor rim and non-neoplastic tissues. These alterations are intimately related and have prognostic effect with stiff, dense tissue correlating with longer progression-free survival. These findings reveal new insights into the spatial heterogeneity of biophysical parameters in the GBM tumor microenvironment and identify a set of characteristics that may correlate with patient prognosis. In the long term, these characteristics may aid in the development of strategies to combat therapeutic resistance. [ABSTRACT FROM AUTHOR]

Quantitative assessment of foods consumed when using 24-hour dietary recall requires accurate tools to estimate portion sizes. Therefore, we developed a food portion photography atlas with age-appropriate portion sizes for 11 foods frequently consumed by young children (sizes for 6-11-month- and for 12-23-month-old children) and women of childbearing age in Ouagadougou, Burkina Faso capital. We then compared the accuracy and precision of portion estimation with this atlas and with salted replicas relative to weighed records (the reference). After weighing, we randomly assigned food portions to 67 women and their children. The next day, women estimated the served portions and leftovers by recall using the atlas and then salted replicas (n = 1156 measurements, ranging from 19 to 113 for each food). For most food types, the portions estimated with the atlas and salted replicas were positively correlated and showed good concordance with the weighed records. However, accuracy and precision varied in function of the estimation method, food type, and age group. The mean crude differences ranged from -28 to +12g (with errors in absolute values from 24 to 69%) for children, and from -32 to +44g (errors from 17 to 56%) for women. The atlas-based method showed the lowest Lin's concordances (coefficients of 0.1 to 0.2) for the leafy vegetable dish, meat, and fish in 12-23-month-old children. Bland-Altman plots indicated that the salted replicas allowed estimating the consumed portions with fewer errors than the photographic atlas (56 to 91% vs 46 to 79% between the limits of ±50%). Our study highlights that mothers have difficulties in perceiving the quantities of food consumed by their children. Our findings also indicate that the food atlas could be used in food consumption surveys when salted replicas are not available for all food types.

Glioblastoma (GBM), the most aggressive brain tumor in human patients, is decidedly heterogeneous and highly vascularized. Glioma stem/initiating cells (GSC) are found to play a crucial role by increasing cancer aggressiveness and promoting resistance to therapy. Recently, cross-talk between GSC and vascular endothelial cells has been shown to significantly promote GSC self-renewal and tumor progression. Furthermore, GSC also transdifferentiate into bona fide vascular endothelial cells (GEC), which inherit mutations present in GSC and are resistant to traditional antiangiogenic therapies. Here we use three-dimensional mathematical modeling to investigate GBM progression and response to therapy. The model predicted that GSCs drive invasive fingering and that GEC spontaneously form a network within the hypoxic core, consistent with published experimental findings. Standard-of-care treatments using DNA-targeted therapy (radiation/chemo) together with antiangiogenic therapies reduced GBM tumor size but increased invasiveness. Anti-GEC treatments blocked the GEC support of GSCs and reduced tumor size but led to increased invasiveness. Anti-GSC therapies that promote differentiation or disturb the stem cell niche effectively reduced tumor invasiveness and size, but were ultimately limited in reducing tumor size because GECs maintain GSCs. Our study suggests that a combinatorial regimen targeting the vasculature, GSCs, and GECs, using drugs already approved by the FDA, can reduce both tumor size and invasiveness and could lead to tumor eradication. Cancer Res; 77(15); 4171-84. ©2017 AACR.

ObjectiveIn glioblastoma, the crosstalk between vascular endothelial cells (VECs) and glioma stem cells (GSCs) has been shown to enhance tumor growth. We propose a multiscale mathematical model to study this mechanism, explore tumor growth under various initial and microenvironmental conditions, and investigate the effects of blocking this crosstalk.MethodsWe develop a hybrid continuum-discrete model of highly organized vascularized tumors. VEC-GSC crosstalk is modeled via vascular endothelial growth factor (VEGF) production by tumor cells and by secretion of soluble factors by VECs that promote GSC self-renewal and proliferation.ResultsVEC-GSC crosstalk increases both tumor size and GSC fraction by enhancing GSC activity and neovascular development. VEGF promotes vessel formation, and larger VEGF sources typically increase vessel numbers, which enhances tumor growth and stabilizes the tumor shape. Increasing the initial GSC fraction has a similar effect. Partially disrupting the crosstalk by blocking VEC secretion of GSC promoters reduces tumor size but does not increase invasiveness, which is in contrast to antiangiogenic therapies, which reduce tumor size but may significantly increase tumor invasiveness.SignificanceMultiscale modeling supports the targeting of VEC-GSC crosstalk as a promising approach for cancer therapy.

Abstract Colorectal cancer and other cancers often metastasize to the liver in later stages of the disease, contributing significantly to patient death. While the biomechanical properties of the liver parenchyma (normal liver tissue) are known to affect tumor cell behavior in primary and metastatic tumors, the role of these properties in driving or inhibiting metastatic inception remains poorly understood, as are the longer-term multicellular dynamics. This study adopts a multi-model approach to study the dynamics of tumor-parenchyma biomechanical interactions during metastatic seeding and growth. We employ a detailed poroviscoelastic model of a liver lobule to study how micrometastases disrupt flow and pressure on short time scales. Results from short-time simulations in detailed single hepatic lobules motivate constitutive relations and biological hypotheses for a minimal agent-based model of metastatic growth in centimeter-scale tissue over months-long time scales. After a parameter space investigation, we find that the balance of basic tumor-parenchyma biomechanical interactions on shorter time scales (adhesion, repulsion, and elastic tissue deformation over minutes) and longer time scales (plastic tissue relaxation over hours) can explain a broad range of behaviors of micrometastases, without the need for complex molecular-scale signaling. These interactions may arrest the growth of micrometastases in a dormant state and prevent newly arriving cancer cells from establishing successful metastatic foci. Moreover, the simulations indicate ways in which dormant tumors could “reawaken” after changes in parenchymal tissue mechanical properties, as may arise during aging or following acute liver illness or injury. We conclude that the proposed modeling approach yields insight into the role of tumor-parenchyma biomechanics in promoting liver metastatic growth, and advances the longer term goal of identifying conditions to clinically arrest and reverse the course of late-stage cancer.

Abstract The pharmacokinetics of nanoparticle-borne drugs targeting tumors depends critically on nanoparticle design. Empirical approaches to evaluate such designs in order to maximize treatment efficacy are time- and cost-intensive. We have recently proposed the use of computational modeling of nanoparticle-mediated drug delivery targeting tumor vasculature coupled with numerical optimization to pursue optimal nanoparticle targeting and tumor uptake. Here, we build upon these studies to evaluate the effect of tumor size on optimal nanoparticle design by considering a cohort of heterogeneously-sized tumor lesions, as would be clinically expected. The results indicate that smaller nanoparticles yield higher tumor targeting and lesion regression for larger-sized tumors. We then augment the nanoparticle design optimization problem by considering drug diffusivity, which yields a two-fold tumor size decrease compared to optimizing nanoparticles without this consideration. We quantify the tradeoff between tumor targeting and size decrease using bi-objective optimization, and generate five Pareto-optimal nanoparticle designs. The results provide a spectrum of treatment outcomes – considering tumor targeting vs. antitumor effect – with the goal to enable therapy customization based on clinical need. This approach could be extended to other nanoparticle-based cancer therapies, and support the development of personalized nanomedicine in the longer term.

Alzheimer's disease (AD) is a neurodegenerative condition that affects the central nervous system and represents 60% to 70% of all dementia cases. Due to an increased aging population, the number of patients diagnosed with AD is expected to exceed 131 million worldwide by 2050. The disease is characterized by various clinical symptoms and pathological features that define three main sequential decline stages, namely, early/mild, intermediate/moderate and late/severe stages. Although it is considered irreversible, early diagnosis of AD is highly desirable to help preserve cognitive function. However, early diagnosis is difficult due to different factors, including the patient-specific development of AD. The main contribution of the proposed work is to present a personalized (i.e., local/brain regional) computer-aided diagnosis (CAD) system for early diagnosis of AD from two perspectives, functional and structural to assist diagnosis. In other words, the proposed system uniquely yields local/regional diagnosis by combining 11C PiB positron emission tomography (11C PiB PET), which provides functional diagnosis, with structural magnetic resonance imaging (sMRI), which provides structural diagnosis. To the best of our knowledge, this is the first work to combine sMRI and the 11C PiB PET for local/regional early diagnosis of AD. The system processes the two modalities through a number of steps: pre-processing, brain labeling (parcellation), feature extraction, and diagnosis. A local/regional diagnosis is presented for each modality separately, followed by the final global diagnosis obtained by integrating the results from the two modalities. Evaluation of the proposed system shows average results of 97.5%, 100%, and 96.77% for accuracy, specificity, and sensitivity, respectively. With further development, it is envisioned that this system could contribute to the early diagnosis of AD in the clinical setting.