Polarity control of carrier injection at ferroelectric/metal interfaces for electrically switchable diode and photovoltaic effects

We investigated a switchable ferroelectric diode effect and its physical mechanism in Pt/BiFeO3/SrRuO3 thin-film capacitors. Our results of electrical measurements support that, near the Pt/BiFeO3 interface of as-grown samples, a defective layer (possibly, an oxygen-vacancy-rich layer) becomes formed and disturbs carrier injection. We therefore used an electrical training process to obtain ferroelectric control of the diode polarity where, by changing the polarization direction using an external bias, we could switch the transport characteristics between forward and reverse diodes. Our system is characterized with a rectangular polarization hysteresis loop, with which we confirmed that the diode polarity switching occurred at the ferroelectric coercive voltage. Moreover, we observed a simultaneous switching of the diode polarity and the associated photovoltaic response dependent on the ferroelectric domain configurations. Our detailed study suggests that the polarization charge can affect the Schottky barrier at the ferroelectric/metal interfaces, resulting in a modulation of the interfacial carrier injection. The amount of polarization-modulated carrier injection can affect the transition voltage value at which a space-charge-limited bulk current-voltage (J-V) behavior is changed from Ohmic (i.e., J ~ V) to nonlinear (i.e., J ~ V^n with n \geq 2). This combination of bulk conduction and polarization-modulated carrier injection explains the detailed physical mechanism underlying the switchable diode effect in ferroelectric capacitors.Comment: Accepted for publication in Phys. Rev.

Judah Folkman, a pioneer in the study of angiogenesis

More than 30 years ago, Judah Folkman found a revolutionary new way to think about cancer. He postulated that in order to survive and grow, tumors require blood vessels, and that by cutting off that blood supply, a cancer could be starved into remission. What began as a revolutionary approach to cancer has evolved into one of the most exciting areas of scientific inquiry today. Over the years, Folkman and a growing team of researchers have isolated the proteins and unraveled the processes that regulate angiogenesis. Meanwhile, a new generation of angiogenesis research has emerged as well, widening the field into new areas of human disease and deepening it to examine the underlying biological processes responsible for those diseases

Multiscale modelling of vascular tumour growth in 3D: the roles of domain size & boundary condition

We investigate a three-dimensional multiscale model of vascular tumour growth, which couples blood flow, angiogenesis, vascular remodelling, nutrient/growth factor transport, movement of, and interactions between, normal and tumour cells, and nutrient-dependent cell cycle dynamics within each cell. In particular, we determine how the domain size, aspect ratio and initial vascular network influence the tumour's growth dynamics and its long-time composition. We establish whether it is possible to extrapolate simulation results obtained for small domains to larger ones, by constructing a large simulation domain from a number of identical subdomains, each subsystem initially comprising two parallel parent vessels, with associated cells and diffusible substances. We find that the subsystem is not representative of the full domain and conclude that, for this initial vessel geometry, interactions between adjacent subsystems contribute to the overall growth dynamics. We then show that extrapolation of results from a small subdomain to a larger domain can only be made if the subdomain is sufficiently large and is initialised with a sufficiently complex vascular network. Motivated by these results, we perform simulations to investigate the tumour's response to therapy and show that the probability of tumour elimination in a larger domain can be extrapolated from simulation results on a smaller domain. Finally, we demonstrate how our model may be combined with experimental data, to predict the spatio-temporal evolution of a vascular tumour

METH-2 silencing and promoter hypermethylation in NSCLC

The antiangiogenic factor METH-2 (ADAMTS-8) was identified in a previous dual-channel cDNA microarray analysis to be at least two-fold under-represented in 85% (28 out of 33) of primary non-small-cell lung carcinomas (NSCLCs). This observation has been validated in an independent series of NSCLCs and adjacent normal tissues by comparative multiplex RT—PCR, and METH-2 mRNA expression was dramatically reduced in all 23 tumour samples analysed. Immunohistochemical analysis of the same sample set demonstrated that METH-2 was strongly expressed in 14 out of 19 normal epithelial sites examined but only one out of 20 NSCLCs. DNA methylation analysis of the proximal promoter region of this gene revealed abnormal hypermethylation in 67% of the adenocarcinomas and 50% of squamous cell carcinomas, indicating that epigenetic mechanisms are involved in silencing this gene in NSCLC. No homozygous deletions of METH-2 were found in lung cancer cell lines. Allelic imbalance in METH-2 was assessed by an intronic single nucleotide polymorphism (SNP) assay and observed in 44% of informative primary samples. In conclusion, the downregulation of METH-2 expression in primary NSCLC, often associated with promoter hypermethylation, is a frequent event, which may be related to the development of the disease

Endostatin expression in pancreatic tissue is modulated by elastase

Pancreatic tumours are scirrhous, avascular tumours, suggesting that they may produce angiogenesis inhibitors that suppress the growth of the vasculature to the tumour and metastases. We have sought evidence for the angiogenesis inhibitor, endostatin, in normal and cancerous pancreatic tissue. Using Western blotting, we found mature 20 kDa endostatin in cancer tissue but not in normal tissue. Several endostatin-related peptides of higher mol wt were present in both tissues. Extracts from normal tissue were able to degrade exogenous endostatin, whereas extracts from cancer were without effect. Although the exocrine pancreas secretes inactive proenzymes of trypsin, chymotrypsin and elastase, their possible role in this degradation was examined. The trypsin/chymotrypsin inhibitor, Glycine max, did not prevent the degradation of endostatin by normal pancreatic extracts but elastatinal, a specific inhibitor of elastase, reduced the rate of degradation. Extracts of pancreatic tumours did not express any detectable elastase activity, but an elastase (Km 1.1 mM) was expressed by extracts of normal pancreas. We conclude that endostatin is present and stable in pancreatic cancer tissues, which may explain their avascular nature, but that normal pancreatic tissue expresses enzymes, including elastase, which rapidly degrade endostatin. The stability of endostatin may have implications for its therapeutic use

Class of self-limiting growth models in the presence of nonlinear diffusion

The source term in a reaction-diffusion system, in general, does not involve explicit time dependence. A class of self-limiting growth models dealing with animal and tumor growth and bacterial population in a culture, on the other hand are described by kinetics with explicit functions of time. We analyze a reaction-diffusion system to study the propagation of spatial front for these models.Comment: RevTex, 13 pages, 5 figures. To appear in Physical Review

Using Machine Learning to Diagnose Misaligned CT Scans

The usage of machine learning has grown exponentially in recent years; However, its applicable uses for medical diagnosis are still in an early stage. Conditions such as Developmental Dysplasia of the Hip (DDH), Cerebral Palsy (CP), and Femoracetabular Impingement (FAI) rely heavily on imaging techniques such as Ultrasound and Computed Tomography (CT) scans. Radiologists use multiple manually computed metrics using these images to diagnose conditions. This is time-intensive and requires an aligned image to get accurate diagnoses. The proposed application uses a deep learning detection algorithm to assist in the metric computation process. The algorithm is implemented using MATLAB R2023A and is trained on CT data gathered from 60 healthy participants. The algorithm performed well on images aligned according to the standard anteroposterior alignment used for radiological measurement. However, the variance of the metrics computation significantly increases when faced with severe misalignment in the craniocaudal or mediolateral axes. Additional algorithm improvements must be made to overcome this increased variance

High Acute Myeloid Leukemia derived VEGFA levels are associated with a specific vascular morphology in the leukemic bone marrow

Acute Myeloid Leukemia (AML) bone marrow biopsies at diagnosis display enhanced angiogenesis and increased VEGFA expression. In a xenograft mouse model it was described that availability of free VEGFA versus bound VEGFA is related to different vascular morphology. In this study we investigate the relationship between vascular morphology within AML bone marrow biopsies and AML derived VEGFA levels. Vessel count and surface area (Chalkley count) were calculated in AML bone marrow biopsies at diagnosis (n = 32), at remission (n = 8) and Normal Bone Marrow (n = 32) using immunohistochemical staining for FVIII, CD31, CTIV, SMA and VEGFA. VEGFA protein levels were measured. High vessel count was associated with an immature vessel status. Combining vessel count and Chalkley count different vessel morphology patterns were quantified within AML bone marrow biopsies. Three different subgroups could be distinguished. The subgroup (37.5% of the samples) exhibiting a high vessel count and vessels with predominantly large lumen (normal Chalkley count) was associated with high secreted VEGFA protein levels. Different vasculature patterns are seen in AML bone marrow biopsies, defined by combining number and size of vessel. These quantified morphology patterns, combined with VEGFA levels, might be of value in the success of VEGF/VEGFR-signaling interference approaches