Search

The identification of immunosuppressive factors within human tumor microenvironments, and the ability to block these factors, would be expected to enhance patients' antitumor immune responses. We previously established that an unidentified factor, or factors, present in ovarian tumor ascites fluids reversibly inhibited the activation of T cells by arresting the T-cell signaling cascade. Ultracentrifugation of the tumor ascites fluid has now revealed a pellet that contains small extracellular vesicles (EV) with an average diameter of 80 nm. The T-cell arrest was determined to be causally linked to phosphatidylserine (PS) that is present on the outer leaflet of the vesicle bilayer, as a depletion of PS-expressing EV or a blockade of PS with anti-PS antibody significantly inhibits the vesicle-induced signaling arrest. The inhibitory EV were also isolated from solid tumor tissues. The presence of immunosuppressive vesicles in the microenvironments of ovarian tumors and our ability to block their inhibition of T-cell function represent a potential therapeutic target for patients with ovarian cancer. Cancer Immunol Res; 3(11); 1269–78. ©2015 AACR.

Fig S1. Delipidation of ascites fluid.

Fig S6. EVs directly inhibit CD4+ and CD8+ T cell activation

Description of additional methods and figure legends for Supplemental Figures

Fig S2. PS/PC liposome titration.

Fig S5. EVs inhibit CD69 upregulation of CD4+ and CD8+ T cells.

Fig S4. Biophysical characterization of exosomes.

Supplementary Data from Rationally Designed Pharmacogenomic Treatment Using Concurrent Capecitabine and Radiotherapy for Glioblastoma; Gene Expression Profiles Associated with Outcome

Purpose: Previous preclinical studies suggested that concurrent capecitabine and radiation could be an effective new treatment modality for glioblastoma (GBM). In the current study, we investigate toxicity and response to this regimen and explore associations between gene expression and patient outcome.Experimental Design: Eighteen newly diagnosed GBM patients received concurrent capecitabine at 625 mg/m2 BID (25% escalation) and irradiation (60 Gy total) for 6 weeks followed by 4 weeks of capecitabine only. Maintenance capecitabine was administered for 14 days every 3 weeks until progression or unacceptable toxicity. Expression analysis of 94 genes involved in capecitabine metabolism and radiation response was done on tissues obtained before therapy. The relationship of gene expression with time-to-progression (TTP) and overall survival (OS) was investigated using univariate Cox proportional hazards regression, semi-supervised principle component analysis, and class prediction modeling.Results: The maximum tolerated dose of capecitabine was 625 mg/m2 BID. Median patient TTP and OS were 247 and 367 days, respectively. Cox regression identified 24 genes significantly (P < 0.025) associated with patient outcome. Semi-supervised principle component analysis identified two patient populations significantly different in both TTP (P = 0.005) and OS (P = 0.015). Class prediction modeling determined that eight genes (RAD54B, MTOR, DCTD, APEX2, TK1, RRM2, SLC29A1, and ERCC6) could collectively classify patients into outcome subgroups with 100% accuracy and precision.Conclusions: Capecitabine and concurrent radiation for newly diagnosed GBM seems to be well tolerated and comparable to temozolomide and radiation. A gene expression profile predictive of patient outcome that may be useful in patient stratification for therapy was also elucidated. Clin Cancer Res; 16(10); 2890–8. ©2010 AACR.

Rare diseases are frequently caused by inherited 'monogenic' defects. Treatment interventions that target a specific genetic location or that replaces a specific protein provide rational therapeutic approaches. The current review discusses innovative targeted therapies that act or modulate at the level of DNA, RNA, or protein. They include DNA gene editing, small interference RNA (siRNA), antisense oligonucleotide (ASO), small molecule RNA splicing modifier, and bispecific antibody. With limited numbers of patients, testing multiple dose levels and regimens prior to making an informed dose decision remains one of the major challenges in rare disease drug development. Clinical pharmacology strategically bridges the gap to support drug development and regulatory approvals. Pharmacokinetic drug exposures are driven by absorption, distribution, metabolism, elimination, and in some cases immunogenicity. Drug responses are measured by pharmacodynamic biomarkers that are linked to either short- or long-term clinical outcomes. Understanding the drug exposure-response relationship lies at the heart of bridging the gap that enables a dose decision by balancing effectiveness and safety. Furthermore, and importantly, understanding the influence of intrinsic and extrinsic factors on drug pharmacokinetics enables dose adjustment decisions based on drug exposures. Case examples include the identification of doses and regimens without a formal dose-finding study, the support of new doses and regimens without conducting additional studies, and the extrapolation of adult drug-drug interaction (DDI) studies to pediatrics without performing a pediatric DDI study. With increasing discoveries of innovative treatment modalities, the responsibility of clinical pharmacologists is expected to grow and enhance the development of novel treatments for rare diseases.

The network of molecular mediators involved in the transmigration of leukocytes to inflamed tissues has been expanding with the identification of new molecules involved in the inflammatory response. We have previously shown using a rat model that Protein Disulfide Isomerase PDIA4 (ERP72) is involved in the inflammatory response to skeletal muscle traumatic injury. In this paper, we report observations suggesting that calsequestrin 2 (CASQ2), another member of the thioredoxin/PDI family, might contribute to the inflammatory response that leads to adhesion and transmigration of leukocytes into injured skeletal muscle. Indeed, real time PCR assay showed that the expression level CASQ2 is significantly enhanced [p2+ buffering role of CASQ2 suggest that the protein contributes to the inflammatory process by providing the Ca2+ needed to activate the inflammasome and the leukocytes adhesion molecules which enhances transmigration of inflammatory cells into the injured muscle.

This study included was conducted during 2017 and 2018 seasons on 21-year- old Balady mandarin trees (Citrus reticulata) budded on sour orange rootstock grown, to investigate the possibility of reducing the amount of mineral fertilizers by using organic and biofertilizers of Balady Mandarin trees. Trees planted at 5x5 meters, grown in clay loam with and irrigated by flood irrigation system. Seven fertilization treatments were applied as follows: 100% mineral NPK fertilizers (control), 100% organic fertilizers (enrichment compost with two natural rocks, rock phosphate and feldspar), 100% biofertilizers (nitrobien, phosphorien and potassiumag), 50% mineral fertilizers + 50% organic fertilizers, 50% mineral fertilizers + 50% biofertilizers, 50% organic fertilizers + 50% biofertilizers and 33.3% mineral fertilizers + 33.3% organic fertilizers + 33.3% biofertilizers. The results indicated that there is a possibility of using organic and biofertilizers as a partial substitute of mineral fertilizers. As this study confirmed the application of mineral, organic and bio-fertilizers at equal ratios (1:1:1) was the best management system for ensuring the best vegetative growth traits, achieving the highest yield with its components, improving the physical and chemical characteristics of fruits and increasing leaf mineral content of Balady Mandarin trees.

This open‐label, phase Ib study (NCT02346370) assessed the effect of pegvorhyaluronidase alfa (PVHA; PEGPH20) on the plasma pharmacokinetics (PKs) and safety of docetaxel in 15 patients with stage IIIB/IV non‐small cell lung cancer (NSCLC). The docetaxel PK profile from this study was consistent with simulations from a published docetaxel population PK model, and did not demonstrate an effect of PVHA on docetaxel PK. A maximum a posteriori Bayesian fit of the literature PK model to the docetaxel PK appeared unbiased. Adverse events (AEs) were generally consistent with previous reports for docetaxel monotherapy in NSCLC, except for higher incidence of musculoskeletal events, including myalgias, with PVHA plus docetaxel. The most common AEs were fatigue (87%), muscle spasms (60%), and myalgia (53%). Four patients experienced thromboembolic events (27%), three leading to treatment discontinuation. PVHA appeared to demonstrate an acceptable safety profile when given with docetaxel without significantly changing the plasma PK of docetaxel in patients with stage IIIB/IV NSCLC.

New therapeutic modalities carry with them great promise for the treatment of rare diseases. They also present unique development challenges including immunogenicity, which can impact the safety and efficacy of those new modalities. In this review, an overview of the basic function of the immune system and its possible interaction with new therapeutic modalities is presented. A juxtaposition of immunogenicity in the rare disease space versus traditional clinical programs is hereby being proposed. A clinical pharmacology viewpoint of immunogenicity, proposed approaches to account for immunogenicity in clinical data, bioanalytical considerations, and effects of route of administration and production changes on immunogenicity are discussed.

Iron-refractory iron deficiency anemia (IRIDA) is considered an autosomal recessive iron deficiency anemia due to mutations in the transmembrane protease serine 6 (TMPRSS6) gene. Variations in iron parameters and a higher risk of iron deficiency have been linked to the TMPRSS6 mutations. Furthermore, human genome-wide association studies (GWAS) identified a common mutation (rs855791) linked to abnormal hematological parameters, highlighting the importance of the TMPRSS6 gene in the regulation of iron homeostasis. This is the first study to investigate TMPRSS6 gene mutation in six Saudi families of probands with iron deficiency anemia unresponsive to oral iron and partially responsive to parenteral iron administration. Each participant provided a vacutainer tube with three blood samples (2.5 ml each) and analyzed based on hematological, biochemical iron profiles, and followed by genotyping by PCR. The TMPRSS6 gene was amplified, sequenced, and analyzed in all probands and family members. Statistical analysis was done using SPSS and SHEsis software. Few functional mutations in these families were suggested (p.W73X, p.E523K and p.V736A). The proband of family 6 presented numerous hematological abnormalities upon initial consultation, including normocytic anemia accompanied by low Hb, normal MCV, low serum iron, low serum ferritin, and normal TIBC. While the p.W73X variant was only found in 2 families, the p.V736A variant was found in all examined Saudi families with IRIDA. Given the evidence outlined for these six cases, future genotype-phenotype correlation studies in a large number of IRIDA patients in Saudi Arabia may be very informative for patient management, in addition to increasing knowledge of TMPRSS6 function during development as well as factors in the regulation of TMPRSS6 and its effect on iron levels in the body.

Leishmaniasis is an infectious disease caused by parasites of the genus Leishmania and transmitted by the bite of a sand fly. To date, most available drugs for treatment are toxic and beyond the economic means of those affected by the disease. Protein disulfide isomerase (PDI) is a chaperone protein that plays a major role in the folding of newly synthesized proteins, specifically assisting in disulfide bond formation, breakage, or rearrangement in all non-native proteins. In previous work, we demonstrated that Leishmania major PDI (LmPDI) has an essential role in pathogen virulence. Furthermore, inhibition of LmPDI further blocked parasite infection in macrophages. In this study, we utilized a computer-aided approach to design a series of LmPDI inhibitors. Fragment-based virtual screening allowed for the understanding of the inhibitors' modes of action on LmPDI active sites. The generated compounds obtained after multiple rounds of virtual screening were synthesized and significantly inhibited target LmPDI reductase activity and were shown to decrease in vitro parasite growth in human monocyte-derived macrophages. This novel cheminformatics and synthetic approach led to the identification of a new series of compounds that might be optimized into novel drugs, likely more specific and less toxic for the treatment of leishmaniasis.

Deep neural networks (DNNs) have surpassed human-level accuracy in various learning tasks. However, unlike humans who have a natural cognitive intuition for probabilities, DNNs cannot express their uncertainty in the output decisions. This limits the deployment of DNNs in mission-critical domains, such as warfighter decision-making or medical diagnosis. Bayesian inference provides a principled approach to reason about model's uncertainty by estimating the posterior distribution of the unknown parameters. The challenge in DNNs remains the multi-layer stages of non-linearities, which make the propagation of high-dimensional distributions mathematically intractable. This paper establishes the theoretical and algorithmic foundations of uncertainty or belief propagation by developing new deep learning models named PremiUm-CNNs (Propagating Uncertainty in Convolutional Neural Networks). We introduce a tensor normal distribution as a prior over convolutional kernels and estimate the variational posterior by maximizing the evidence lower bound (ELBO). We start by deriving the first-order mean-covariance propagation framework. Later, we develop a framework based on the unscented transformation (correct at least up to the second-order) that propagates sigma points of the variational distribution through layers of a CNN. The propagated covariance of the predictive distribution captures uncertainty in the output decision. Comprehensive experiments conducted on diverse benchmark datasets demonstrate: 1) superior robustness against noise and adversarial attacks, 2) self-assessment through predictive uncertainty that increases quickly with increasing levels of noise or attacks, and 3) an ability to detect a targeted attack from ambient noise.

Nowadays, polypropylene plastics are very often found and cause various environmental problems. Though it is known that along with polypropylene itself comes from propylene monomers obtained from refining petroleum. Besides the use of waste cooking, biodiesel fuel has many drawbacks, one of which is power and fuel consumption. Mixing polypropylene plastic waste for reuse with waste cooking oil biodiesel is an option. This study uses five variations of fuel, namely HSD, B30, C20, C30, and C40, a combination of HSD, waste cooking, and polypropylene. This research is based on experiments to analyze the impact of using these five variations of fuel on the performance diesel engines based on simulation. The performance of the diesel engine would be measured to SFOC, power, and torque produced by each fuel. Based on the results of the analysis of the performance of the diesel engine performance of C20, fuel can be the most optimum alternative fuel to the substitute B30, producing 6.0 kW of power, 238gr / kWh of SFOC, and 31.7Nm of torque.

To evaluate the duration of effect of rHuPH20 on SC absorption of cetuximab and to develop a mechanistic pharmacokinetic model linking the kinetics of rHuPH20 action with hyaluronan (HA) homeostasis and absorption of cetuximab from the SC space.Serum pharmacokinetics of cetuximab was evaluated after IV and SC dosing at 0.4 and 10 mg/kg (control groups). In test groups, SC cetuximab was administered simultaneously with rHuPH20 (Co-Injection) or 12 h after injection of rHuPH20 (Pre-Injection). Mechanistic pharmacokinetic model was developed to simultaneously capture cetuximab kinetics in all groups.Administration of rHuPH20 resulted in a faster absorption of cetuximab; the difference between co-injection and pre-injection groups appeared to be dependent on the dose level. The model combined three major components: kinetics of rHuPH20 at SC site; HA homeostasis and its disruption by rHuPH20; and cetuximab systemic disposition and the effect of HA disruption on cetuximab SC absorption. The model provided good description of experimental data obtained in this study and collected previously.Proposed model can serve as a potential translational framework for capturing the effect of rHuPH20 across multiple preclinical species and in human studies and can be used for optimization of SC delivery of biotherapeutics.

Background Shoulder impingement syndrome is a common cause of shoulder pain in primary health care settings. Many physical modalities of treatment are available in clinical practice, however there is insufficient evidence on their relative effectiveness. This review compares the effectiveness of Low Level Laser Therapy (LLLT) with ultrasonic therapy. Objectives To assess the effectiveness of LLLT vs. ultrasonic therapy in patients with subacromial impingement syndrome Search methods We searched Cochrane Central Register of Controlled Trials (CENTRAL) on the Cochrane Library, MEDLINE (Pubmed), Embase, Scopus. We searched trials registries on ClinicalTrials.gov (www.ClinicalTrials.gov) and the WHO International Clinical Trials Registry Platform (ICTRP) Search Portal (apps.who.int/trialsearch/). We also hand-searched reference lists of all included primary studies, relevant conference proceedings and academic literature, and relevant systematic reviews (both Cochrane and non Cochrane), to identify additional studies missed from the original electronic searches (e.g., unpublished or in press citations). We did not use date or language restrictions. Selection criteria Randomized controlled trials comparing LLLT vs. US therapy in adult patients with subacromial impingement syndrome. Data collection Two authors independently assessed trial quality and extracted data. We contacted study authors for additional information. We collected our primary outcomes information from the trials and assessed the quality of evidence for key outcomes using GRADE. Results We included 2 RCTs, contributing 67 participants to our qualitative synthesis. The overall risk of bias is high for both studies. Very low-quality evidence from 1 RCT shows slightly increased mean change in pain severity after LLLT compared to ultrasonic therapy in the short term (3 months) (MD 4.69, 95% CI -5.76 to -3.62).[13]. Very low-quality evidence from 1 RCT shows little to no difference in functional improvement after LLLT compared to ultrasonic therapy in the short term (after 3 months) (MD -0.63, 95% CI -5.53 to 4.27) [13]. No studies investigated Range of Motion in the short term. Verylow certainty evidence showed little to no difference in pain severity and function in the immediate post-treatment phase (up to 1 month). No studies addressed long term follow-up. conclusion There is insufficient evidence regarding the difference in effects between LLLT and Ultrasonic therapy for the treatment of shoulder impingement syndrome.

PURPOSE Multi-parametric MRI and artificial intelligence (AI) methods were previously used to predict peritumoral neoplastic cell infiltration and risk of future recurrence in glioblastoma, in single-institution studies. We hypothesize that important characteristics of peritumoral tissue heterogeneity captured, engineered/selected, and quantified by these methods relate to predictions generalizable in the multi-institutional ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium. METHODS To support further development, generalization, and clinical translation of our proposed method, we trained the AI model on a retrospective cohort of 29 de novo glioblastoma patients from the Hospital of the University of Pennsylvania (UPenn) (Male/Female:20/9, age:22-78 years) followed by evaluation on a prospective multi-institutional cohort of 84 glioblastoma patients (Male/Female:51/33, age:34-89 years) from Case Western Reserve University/University Hospitals (CWRU/UH, 25), New York University (NYU, 13), Ohio State University (OSU, 13), University Hospital Río Hortega (RH, 2), and UPenn (31). Features extracted from pre-resection MRI (T1, T1-Gd, T2, T2-FLAIR, ADC) were used to build our model predicting the spatial pattern of subsequent tumor recurrence. These predictions were evaluated against regions of pathology-confirmed post-resection recurrence. RESULTS Our model predicted the locations that later harbored tumor recurrence with sensitivity 83%, AUC 0.83 (99% CI, 0.73-0.93), and odds ratio 7.23 (99% CI, 7.09-7.37) in the prospective cohort. Odds ratio (99% CI)/AUC(99% CI) per institute were: CWRU/UH, 7.8(7.6-8.1)/0.82(0.75-0.89); NYU, 3.5(3.3-3.6)/0.84(074-0.93); OSU, 7.9(7.6-8.3)/0.8(0.67-0.94); RH, 22.7(20-25.1)/0.94(0.27-1); UPenn, 7.1(6.8-7.3)/0.83(0.76-0.91). CONCLUSION This is the first study that provides relatively extensive multi-institutional validated evidence that AI can provide good predictions of peritumoral neoplastic cell infiltration and future recurrence, by dissecting the MRI signal heterogeneity in peritumoral tissue. Our analyses leveraged the unique dataset of the ReSPOND consortium, which aims to develop and evaluate AI-based biomarkers for individualized prediction and prognostication, by moving from single-institution studies to generalizable, well-validated multi-institutional predictive biomarkers.

This study included two different experiments; the first aims to investigate the possibility of reducing the amount of mineral fertilizers by using organic and biofertilizers of Balady Mandarin trees. The second experiment aims to examine postharvest treatments on storability of Balady Mandarin fruits. The first experiment included seven treatments: 100% mineral NPK fertilizers (control), 100% organic fertilizers (enrichment compost with two natural rocks, rock phosphate and feldspar), 100% biofertilizers (nitrobien, phosphorien and potassiumag), 50% mineral fertilizers + 50% organic fertilizers, 50% mineral fertilizers + 50% biofertilizers, 50% organic fertilizers + 50% biofertilizers and 33.3% mineral fertilizers + 33.3% organic fertilizers + 33.3% biofertilizers. The results indicated that there is a possibility of using organic and biofertilizers as a partial substitute of mineral fertilizers. As this study confirmed the application of mineral, organic and bio-fertilizers at equal ratios (1:1:1) was the best management system for ensuring the best vegetative growth traits, achieving the highest yield with its components, improving the physical and chemical characteristics of fruits and increasing leaf mineral content of Balady Mandarin trees. The second experiment included ten postharvest treatments by dipping the fruits for three minutes in each of the used materials as follows: distilled water (control), 10% Arabic gum, 6% Bio Arc, bio-agent fungicide, 0.3% Potassium Sorbate, 2% Potassium Carbonate, 2% Mono Potassium Phosphate, 10% Arabic gum + 6% Bio Arc, 10% Arabic gum + 0.3% Potassium Sorbate, 10% Arabic gum + 2% Potassium Carbonate and 10% Arabic gum + 2% Mono Potassium Phosphate. The results showed that fruit dipping in 10% arabic gum plus 2% mono potassium phosphate is an effective treatment for reducing the rate of deterioration and as well for the retaining the quality attributes during extended cold storage at 5°C and 90-95% relative humidity for 60 days of Balady Mandarin fruits.

The vascular inflammatory response involves the coordinated action of a large network of molecular mediators and culminates in the transmigration of leukocytes into the site of inflammation. Inflammatory mediators include a variety of protein families, including adhesion molecules such as integrins and members of the immunoglobulin superfamily, as well as other cytokines and chemokines. In this study, a rat model of traumatic skeletal muscle injury was used to demonstrate endoplasmic reticulum resident protein 72 (ERp72) overexpression in the early phase of the inflammatory response that follows skeletal muscle injury. Reverse transcription‑quantitative PCR, western blotting, dual‑labeling immunohistochemistry and immunofluorescence experiments confirmed that ERp72 was expressed on the endothelial cells of blood vessels present at the injured area. In addition, a cell‑based neutrophil adhesion assay indicated that a polyclonal antibody specific for ERp72 significantly reduced adhesion of neutrophils to activated human umbilical vein endothelial cells (35% reduction). These data suggested that ERp72 expression on vascular endothelial cells may play a role in skeletal muscle inflammation and could be considered as a target for the modulation of leukocyte‑endothelial cell interactions in an inflammatory setting.

Brain tumor segmentation refers to the process of pixel-level delineation of brain tumor structures in medical images, such as Magnetic Resonance Imaging (MRI). Brain tumor segmentation is required for radiotherapy treatment planning and can diagnosis through surveillance. Automatic segmentation of brain tumors is a challenging problem due to the complex topology of anatomical structures, noise from image acquisition, heterogeneity of signals and spatial/structural variations of tumors. Machine Learning (ML) techniques, including Deep Artificial Neural Networks (DNNs), have shown significant improvement in classification and segmentation tasks. This chapter provides a comprehensive review of supervised learning models and architectures for image segmentation. A particular emphasis will be placed on U-Net and U-Net with Inception and dilated Inception modules for brain tumor segmentation. The performance of the proposed models is evaluated using the multi-modal BRAin Tumor Segmentation (BRATS) benchmark dataset. Furthermore, we present a new Bayesian deep learning framework, called extended Variational Density Propagation (exVDP), for quantifying uncertainty in the decision of DNNs. In particular, exVDP provides a pixel-level uncertainty map associated with the network’s segmentation output. Finally, we present clinical retrospective studies in tumor surveillance using MRI data from patients with glioma and show the advantages accrued from these methods.

No clear guidelines exist for the appropriate diagnostic workup of an intracranial mass suspected to be a metastasis from unknown primary origin. Dural metastasis from prostatic origin is very rare. Patients with a known history of metastatic prostate cancer who present with a newly discovered lesion on brain imaging require neurosurgical biopsy to confirm diagnosis prior to initiating treatment. Intracranial metastasis from prostate cancer is rare, and dural metastasis is rarer than intraparenchymal metastasis. Current consensus guidelines support immunohistochemical staining with classic markers such as prostate-specific antigen (PSA) to identify prostatic origin. However, PSA detection of prostate metastases declines with higher Gleason scores and in patients undergoing androgen deprivation therapy. NKX3.1 is another stain that is highly sensitive and specific for prostate. Our patient was a 54-year-old man with a history of metastatic prostate cancer who presented with new-onset seizures. Brain imaging revealed a dural-based lesion with surrounding vasogenic edema and midline shift. The patient underwent resection of the lesion, which was stained with multiple cancer markers. Prostate-specific antigen was negative, but NKX3.1 was positive indicating a prostatic origin for the mass. He underwent a craniectomy to remove the lesion and was given steroids. However, he succumbed to his illness several months later. Here, we document the first report to our knowledge of a patient with prostate metastasis to the dura that is PSA negative, but NKX3.1 positive.

Background Most existing algorithms for modeling and analyzing molecular networks assume a static or time-invariant network topology. Such view, however, does not render the temporal evolution of the underlying biological process as molecular networks are typically “re-wired” over time in response to cellular development and environmental changes. In our previous work, we formulated the inference of time-varying or dynamic networks as a tracking problem, where the target state is the ensemble of edges in the network. We used the Kalman filter to track the network topology over time. Unfortunately, the output of the Kalman filter does not reflect known properties of molecular networks, such as sparsity. Results To address the problem of inferring sparse time-varying networks from a set of under-sampled measurements, we propose the Approximate Kernel RecONstruction (AKRON) Kalman filter. AKRON supersedes the Lasso regularization by starting from the Lasso-Kalman inferred network and judiciously searching the space for a sparser solution. We derive theoretical bounds for the optimality of AKRON. We evaluate our approach against the Lasso-Kalman filter on synthetic data. The results show that not only does AKRON-Kalman provide better reconstruction errors, but it is also better at identifying if edges exist within a network. Furthermore, we perform a real-world benchmark on the lifecycle (embryonic, larval, pupal, and adult stages) of the Drosophila Melanogaster. Conclusions We show that the networks inferred by the AKRON-Kalman filter are sparse and can detect more known gene-to-gene interactions for the Drosophila melanogaster than the Lasso-Kalman filter. Finally, all of the code reported in this contribution will be publicly available.

This paper represents an electrical modeling of a photovoltaic water pumping system composed of photovoltaic panels. The system reassures electrical energy generation applying a DC buck converter in order to supply a DC motor to pump water. Known for its optimal electrical and physical properties, the super capacitor is integrated into the PV pumping system to allow storing electrical energy and powering the pumping motor at nights and cloudy days. The implementation of the perturbation and observation algorithm in the DC buck converter reassures the system’s operation around the maximum power point produced by the photovoltaic panel. Moving from quantity problem to quality problem, several internal and external factors can infect the stability of the PV pumping system and disrupt its operation around nominal point. On account of this, a pole placement technique is proposed in this paper. This technique is advocated not only for its simple processing and rapid execution, but also for being based on the conversion of the electrical model of the PV pumping system into a mathematical model that comprises matrix equations. This energy conversion process allows variations in output values in proportion to the input evolution along with positioning the system’s poles in the stable points of the S-plane. The equation of this technique applied to the photovoltaic pumping system is indicated in this paper having its program created in Matlab and installed in PLC S7-200 on account of its ability to monitor the inputs instantaneously and modify the outputs in a way proportional to the installed program. Subsequently, the validation of the robustness of this technique is reassured by the comparison between the simulation in Matlab and the experimental tests carried out in sunny periods having the engine powered by photovoltaic panels, and shaded periods where power supply is reassured by the super capacitor.

PURPOSE Multi-parametric MRI based radiomic signatures have highlighted the promise of artificial intelligence (AI) in neuro-oncology. However, inter-institution heterogeneity hinders generalization to data from unseen clinical institutions. To this end, we formulated the ReSPOND (Radiomics Signatures for PrecisiON Diagnostics) consortium for glioblastoma. Here, we seek non-invasive generalizable radiomic signatures from routine clinically-acquired MRI for prognostic stratification of glioblastoma patients. METHODS We identified a retrospective cohort of 606 patients with near/gross total tumor resection ( >90%), from 13 geographically-diverse institutions. All pre-operative structural MRI scans (T1,T1-Gd,T2,T2-FLAIR) were aligned to a common anatomical atlas. An automatic algorithm segmented the whole tumors (WTs) into 3 sub-compartments, i.e., enhancing (ET), necrotic core (NC), and peritumoral T2-FLAIR signal abnormality (ED). The combination of ET+NC defines the tumor core (TC). Quantitative radiomic features were extracted to generate our AI model to stratify patients into short- (< 14mts) and long-survivors ( >14mts). The model trained on 276 patients from a single institution was independently validated on 330 unseen patients from 12 left-out institutions, using the area-under-the-receiver-operating-characteristic-curve (AUC). RESULTS Each feature individually offered certain (limited but reproducible) value for identifying short-survivors: 1) TC closer to lateral ventricles (AUC=0.62); 2) larger ET/brain (AUC=0.61); 3) larger TC/brain (AUC=0.59); 4) larger WT/brain (AUC=0.55); 5) larger ET/WT (AUC=0.59); 6) smaller ED/WT (AUC=0.57); 7) larger ventricle deformations (AUC=0.6). Integrating all features and age, through a multivariate AI model, resulted in higher accuracy (AUC=0.7; 95% C.I.,0.64-0.77). CONCLUSION Prognostic stratification using basic radiomic features is highly reproducible across diverse institutions and patient populations. Multivariate integration yields relatively more accurate and generalizable radiomic signatures, across institutions. Our results offer promise for generalizable non-invasive in vivo signatures of survival prediction in patients with glioblastoma. Extracted features from clinically-acquired imaging, renders these signatures easier for clinical translation. Large-scale evaluation could contribute to improving patient management and treatment planning. *Indicates equal authorship.

Global asymptotic stability is of importance from a theoretical as well as an application point of view in several fields. We study a system of cubic polynomials that models biological networks. We classify the equilibria and show that the property that the interconnection matrix is Lyapunov diagonally stable is a key feature that determines convergence to a single equilibrium. The results are applied to chains of negative edges, cycles, and to interconnected graphs. We give numerical examples and study network graphs obtained from a model of the Drosophila circadian clock.

We have synthesized and used several natural dyes such as extracted from: Spinach, Beet, Henna, Strawberry, Red cabbage, and Mloukhia. The absorption of the extracted dyes diluted in ethanol or distilled water were measured using UV–Vis spectrophotometer. We have studied the topology of these films by scanning electron microscope (SEM), X-ray photoelectron spectroscopy (XPS) and x-ray diffraction (XRD) patterns of synthesized TiO2. The contents of Ti and O of synthesized TiO2 are 30 % and 50 % corresponding to closely Ti4+ state. The absorption of the TiO2 thin films immersed in these dyes was also measured in order to tune the change. The absorption in Beet and Red cabbage is more significant compared to other natural dyes.

Objective/background Mutations in transmembrane protease serine 6 (TMPRSS6) gene induce high hepcidin level, which causes iron-refractory iron deficiency anemia (IRIDA) by preventing duodenal iron absorption. This study aims to identify the common genetic variations of the TMPRSS6 gene that affect iron levels among Saudi female patients with iron deficiency anemia (IDA). Methods All study participants were Saudi females (12–49 years old): 32 patients with IDA, 32 patients with IRIDA, and 34 healthy individuals comprising the control group. Hematological investigations, iron profile, serum hepcidin level, and TMPRSS6 gene transcription were determined. The TMPRSS6 gene was amplified, sequenced, and analyzed among all study participants. Results The mean hepcidin and TMPRSS6 RNA transcription levels in IDA and IRIDA groups were significantly lower than those in the control group. TMPRSS6 gene sequence analysis detected 41 variants: two in the 5′ untranslated region (5′UTR), 17 in introns, and 22 in exons. Thirty-three variants were previously reported in the Single Nucleotide Polymorphism Database, and eight variants were novel; one novel variant was in 5′UTR (g.-2 T > G); five novel variants were detected in exons (p.W73X, p.D479N, p.E523K, p.L674L, and p.I799I). At the time of the sequence analysis of our samples, two variants—p.D479N and p.674L—were novel. However, these variants are present at a very low allele frequency in other populations (L674L, 0.00007761 and D479N, 0.000003980). Conclusion This is the first study to investigate the genetic variants of TMPRSS6 gene in Saudi female patients with IDA. The generated data will serve as a reference for future studies on IDA in the Arab population.

Magnetic resonance images of brain tumors are routinely used in neuro-oncology clinics for diagnosis, treatment planning, and post-treatment tumor surveillance. Currently, physicians spend considerable time manually delineating different structures of the brain. Spatial and structural variations, as well as intensity inhomogeneity across images, make the problem of computer-assisted segmentation very challenging. We propose a new image segmentation framework for tumor delineation that benefits from two state-of-the-art machine learning architectures in computer vision, i.e., Inception modules and U-Net image segmentation architecture. Furthermore, our framework includes two learning regimes, i.e., learning to segment intra-tumoral structures (necrotic and non-enhancing tumor core, peritumoral edema, and enhancing tumor) or learning to segment glioma sub-regions (whole tumor, tumor core, and enhancing tumor). These learning regimes are incorporated into a newly proposed loss function which is based on the Dice similarity coefficient (DSC). In our experiments, we quantified the impact of introducing the Inception modules in the U-Net architecture, as well as, changing the objective function for the learning algorithm from segmenting the intra-tumoral structures to glioma sub-regions. We found that incorporating Inception modules significantly improved the segmentation performance (p < 0.001) for all glioma sub-regions. Moreover, in architectures with Inception modules, the models trained with the learning objective of segmenting the intra-tumoral structures outperformed the models trained with the objective of segmenting the glioma sub-regions for the whole tumor (p < 0.001). The improved performance is linked to multiscale features extracted by newly introduced Inception module and the modified loss function based on the DSC.

Declaration of several large ports as Greenport indicates that increasing the environmental concern of port operatio n in Indonesia. Harbour tug as one of the port’s operational supports is also required to contribute low emissions. One method to reduce exhaust emissions from tugboats is to replace the use of fuel oil with natural gas. This study describes the conceptual design of a dual-fuel LNG system at the harbour tug vessel for operational needs at the Indonesian port. The 2x2500 HP Harbour Tug, which is the case in this study, uses a dual fuel diesel engine as a prime mover with a direct mechanical propulsion system. Study optimization considering the operational mode of a prime mover will determine the LNG storage capacity, due to harbour tug vessel operation and space capacity as well as of bunkering system. The design parameters for the main components of the fuel system, such as the Regasification Unit, Gas Valve Unit are essential considerations to support the system’s operation optimally.

Millimeter waves (MMWs), operating at 30–300 GHz band, are very promising to the next-generation 5G wireless communication systems, enabling data rates of multi Gbps per user. Photonic technology is increasingly considered to play a key role in a wide range of MMW devices, modules, and subsystems that are essential to successfully build next generation MMW-based 5G networks. This work considers the switching function of MMWs exploiting nonlinearity in photonic devices. In this paper, we perform a systematic investigation of the optimum operating conditions that enable an optical single sideband wavelength conversion, by exploiting the nonlinear effects in a semiconductor optical amplifier (SOA). This principle of switching carefully exploits SOA’s four-wave mixing, cross-gain modulation in addition to self-phase modulation effects. The key parameters under investigation include the injection current, the wavelength spacing between the probe and the pump signals in addition to their respective powers. We experimentally determine the optimal operating conditions that maximize the sideband suppression ratio and simultaneously reduce the useless left sideband signal intensity, leading to a dispersion free transmission in optical fiber. Further, we experimentally demonstrate a photonic-based MMW switch of MMW signals having 30 GHz frequency and carrying 3 Gbaud/QPSK modulated signals. A 14-dB sideband suppression ratio of modulated signal is reported.

Determine the safety of tug operation at sea, especially in narrow shipping areas such as port areas, it is necessary to pay attention to the maneuverability of ships and the performance of the ship’s steering system. In ship maneuvering, a specially designed thruster with 360 degrees side thrust with a small turning angle is needed in order to produce a good ship movement performance. In this study, the authors designed a tugboat propeller ka-series four blades. The propeller can move 360 degrees so that the distribution of power is evenly distributed in all directions. The system is expected to provide extra thrust when needed in the process of maneuvering and docking the ship. Equipped with hydraulics used to quickly lift and lower the thruster and pull it back into the hull when not in use. The analysis results show that each propeller variation such as the difference in thrust value, torque value and resulting efficiency. From the analysis model, the highest thrust value was obtained in the first propeller model with a variation of P/D 1, AE/A0 0.45 valued at 306201.4. The lowest torque value is generated in the third propeller model with a variation of P/D 0.6, AE/A0 0.65 value at - 22400.2 Nm. Harbourtug requires a high thrust value, so it is advisable to use the first Propeller model with variations of P/D 1, AE/A0 0.45 The highest efficiency value is obtained in the first propeller model valued at 0.7151.

Data plenitude is the bottleneck for data-driven approaches, including neural networks. In particular, Convolutional Neural Networks (CNNs) require an abundant database of training images to achieve a desired high accuracy. Current techniques employed for boosting small datasets are data augmentation and synthetic data generation, which suffer from computational complexity and imprecision compared to original datasets. In this paper, we intercalate prior knowledge based on spatial relation between images in the third dimension by computing the gradient of subsequent images in the dataset to remove extraneous information and highlight subtle variations between images. The approach is coined “Inverted Cone” because the volume of brain images below the level of the eyes is ordered to form an inverted cone geometry. The application explored in this work is deboning, or brain extraction, in brain magnetic resonance imaging (MRI) scans. The difficulty of obtaining ground truth for this application prevents the ability of obtaining a large quantity of training images to train the CNN. We considered a limited dataset of 23 patients with and without malignant glioblastoma. Deboning was performed by employing an optimized CNN architecture with and without the Inverted Cone processing. The classic CNN without prior knowledge achieved a validation accuracy of 77%, while the Inverted Cone CNN model achieved a validation accuracy of 86% in a dataset of 451 brain MRI slices.

Gliomas are malignant brain tumors that are associated with high neurological morbidity and poor outcomes. Patients diagnosed with low-grade gliomas are typically followed by a sequence of measurements of the tumor size. Here, we show the promise of Long Short-Term Memory Neural Networks (LSTMs) to address two important clinical questions in low-grade gliomas: 1) classification and prediction of future behavior; and 2) early detection of dedifferentiation to a higher grade or more aggressive growth. We use a system of partial differential equations (PDEs), from our earlier work, to generate simulated growth of low-grade gliomas with different clinical parameters. We design an LSTM network to solve the inverse problem of PDE parameter estimation. We find that accuracy increases as a function of the number of tumor measurements and perplexity can also be used to detect a change in tumor grade. These findings highlight the potential usefulness of LSTMs in solving inverse clinical problems.

Melanoma is an aggressive cancer whose incidence continues to rise worldwide; furthermore, metastatic melanoma is associated with poor prognosis. Wnt signaling may lead to conflicting effects on the biology of melanoma as it may either decrease or increase the incidence of metastasis. Here, we show that Wnt5a enhances motility in 3/5 cell lines and represses motility in the other two. We measured the effects of perturbations of the levels of Wnt5a, HADHB, Pirin, and Mart1 on the levels of the seven molecules, Wnt5a, HADHB, Pirin, Mart1, Ret1, Stc2, and S100B in the five cell lines. The results uncovered unanticipated nonlinear molecular dynamics. Seeking a mechanistic explanation, we built network models consisting of ordinary differential equations representing signed directed graphs of the interactions between the seven molecules in the five cell lines. Simulations validate the results of the perturbation experiments and reveal that the indirect network-mediated effects of a molecule on another may annul or reverse its direct effects. Furthermore, network analysis and biological validation link HADHB and Pirin to motility. In summary, the findings reveal: 1) opposite effects of Wnt5a on motility in melanomas, 2) HADHB and Pirin control motility through their effects on Wnt5a, and 3) molecular targeting yields nontrivial nonlinear molecular dynamics, which are not readily anticipated. Citation Format: Mohammed Rasheed, Nidhal Bouaynaya, Lita M. Araysi, Tang Zhuo, Mei Li, Ping Zhou, Kareem El-Kattan, Hassan Fathallah-Shaykh. Networks dynamics and opposite effects of Wnt5a on motility in melanomas. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-32.

Glioblastoma multiforme (GBM) causes significant neurological morbidity and short survival times. Brain invasion by GBM is associated with poor prognosis. Recent clinical trials of bevacizumab in newly-diagnosed GBM found no beneficial effects on overall survival times. We have reported a mathematical model of GBM growth and invasion, built at the scale of clinical magnetic resonance imaging. Here, we replicate the patterns of progression of GBM patients treated with bevacizumab. The model is interrogated to derive a mechanistic explanation for each type of recurrence. Citation Format: Elizabeth Scribner, Olivier Saut, Thierry Colin, Hassan M. Fathallah-Shaykh. Mechanisms of GBM progression on bevacizumab: Model predictions. [abstract]. In: Proceedings of the AACR Special Conference on Computational and Systems Biology of Cancer; Feb 8-11 2015; San Francisco, CA. Philadelphia (PA): AACR; Cancer Res 2015;75(22 Suppl 2):Abstract nr B2-18.

The identification of immunosuppressive factors within human tumor microenvironments, and the ability to block these factors, would be expected to enhance patients' antitumor immune responses. We previously established that an unidentified factor, or factors, present in ovarian tumor ascites fluids reversibly inhibited the activation of T cells by arresting the T-cell signaling cascade. Ultracentrifugation of the tumor ascites fluid has now revealed a pellet that contains small extracellular vesicles (EV) with an average diameter of 80 nm. The T-cell arrest was determined to be causally linked to phosphatidylserine (PS) that is present on the outer leaflet of the vesicle bilayer, as a depletion of PS-expressing EV or a blockade of PS with anti-PS antibody significantly inhibits the vesicle-induced signaling arrest. The inhibitory EV were also isolated from solid tumor tissues. The presence of immunosuppressive vesicles in the microenvironments of ovarian tumors and our ability to block their inhibition of T-cell function represent a potential therapeutic target for patients with ovarian cancer. Cancer Immunol Res; 3(11); 1269–78. ©2015 AACR.

The role of aggregates in the immunogenicity of biologics is a major concern. A recent US FDA guidance on the issue suggests that a gap in knowledge exists regarding the type and size of aggregates involved in the immunogenicity of biologics. Furthermore, the guidance suggests that current techniques cannot capture the crucial stages of protein aggregation. Using a protein unfolding model developed earlier, we generated and classified aggregates of two therapeutic antibodies based on size and conformation. The immunogenic potential of these aggregates were then tested in a murine model. Our findings show that small native-like oligomeric aggregates (

Background This phase I study aimed to evaluate safety, maximum tolerated dose, pharmacokinetics, pharmacodynamics, and preliminary efficacy of voxtalisib (SAR245409, XL765), a pan-class I phosphoinositide 3-kinase (PI3K) and mammalian target of rapamycin (mTOR) inhibitor, in combination with temozolomide (TMZ), with or without radiation therapy (RT), in patients with high-grade glioma. Methods Patients received voxtalisib 30-90 mg once daily (q.d.) or 20-50 mg twice daily (b.i.d.), in combination with 200 mg/m(2) TMZ (n = 49), or voxtalisib 20 mg q.d. with 75 mg/m(2) TMZ and RT (n = 5). A standard 3 + 3 dose-escalation design was used to determine the maximum tolerated dose. Patients were evaluated for adverse events (AEs), plasma pharmacokinetics, pharmacodynamic effects in skin biopsies, and tumor response. Results The maximum tolerated doses were 90 mg q.d. and 40 mg b.i.d. for voxtalisib in combination with TMZ. The most frequently reported treatment-related AEs were nausea (48%), fatigue (43%), thrombocytopenia (26%), and diarrhea (24%). The most frequently reported treatment-related grade ≥3 AEs were lymphopenia (13%), thrombocytopenia, and decreased platelet count (9% each). Pharmacokinetic parameters were similar to previous studies with voxtalisib monotherapy. Moderate inhibition of PI3K signaling was observed in skin biopsies. Best response was partial response in 4% of evaluable patients, with stable disease observed in 68%. Conclusions Voxtalisib in combination with TMZ with or without RT in patients with high-grade gliomas demonstrated a favorable safety profile and a moderate level of PI3K/mTOR pathway inhibition.

The characteristics of titanium (Ti) or molybdenum (Mo) as Schottky contact of device based on 4H-SiC material were investigated. The parameters deduced from static characterisation of Ti/4H-SiC show an increase of barrier height (ϕB) from 0.76 to 1.26 eV and a decrease of ideality factor (n) from 1.26 to 1.07 when the temperature varies from 10 to 460 K. Whereas in the Mo/4H-SiC the barrier height increases from 0.45 to 1.05 eV and the ideality factor decreases from 2.20 to 1.03. When the temperature decreases, a deformation of J–V characteristics appears for T

We have employed several natural dyes for application in dye sensitized solar cells (DSSC). Spinach, beet, red cabbage and strawberry are well known and have been already used. We then checked the opportunity to realize good DSSC with dyes available in Tunisia: Henna and Mallow (Mloukhya). Henna is a herb which has interesting reddish brownish dyeing properties used since antiquity for traditional decoration of skin, hair and fingernails in the Middle East and North Africa. The mallow is a green vegetable which is widely consumed in the same region. The optical absorption of the extracted dyes diluted in ethanol or distilled water were measured using UV–Vis spectrophotometer. The absorption in beet and red cabbage is more significant compared to the other dyes. Mallow and henna dyes present a noticeable band in the region 660 nm. Infra-red spectroscopy measurements were done to probe the structure and dynamics in our used dyes. In this paper, we present the steps followed in the making of our solar cells. The DSSC were assembled using two glass plates (supporting electrode and counter electrode) which are coated with transparent conducting oxide (TCO). The counter electrode is coated by a catalyst Pt (Platinum) to speed up the redox reaction with the electrolyte solution. The typical J–V curves of our solar cells under AM 1.5 using a density of power 100 mW/cm2 were measured. Cells using henna and mallow as dyes present less degradation with time in the photoelectric characteristics. The mallow cell shows a good fill factor of 55% and a noticeable photoelectric conversion efficiency of 0.215%.