Sander Stuijk
email: s.stuijk@tue.nl

Twan Basten

Bart Mesman

Marc Geilen

Predictable embedding of large data structures in multiprocessor networks-on-chip (extended abstract)

This extended abstract presents models to derive timing and resource usage numbers for an application when distant, shared memories are used in an important class of future embedded platforms, namely network-on-chip-based multiprocessors.

Introduction

Real-time requirements in media systems have put the main focus on predicting the timing behavior of complex media systems. This has led to the development of predictable, tile-based multiprocessor networks-on-chip. Each tile contains one or a few processors and local memories [START_REF] Culler | Parallel Computer Architecture: A Hardware/Software Approach[END_REF]. These memories are typically too small to store large data structures (e.g. a video frame). A solution to this is to add tiles with large memories to the architecture. The memories will be distant and shared among potentially many computational resources. We use the terms local and remote to refer to the local processing tile or remote memory tile and their components.

Approach

To get a system with predictable timing properties, we need an appropriate design flow. The starting point of this flow is an SDF model of the application and a predictable architecture. Synchronous dataflow (SDF) and Boolean dataflow (BDF) [START_REF] Buck | Scheduling Dynamic Dataflow Graphs with Bounded Memory using the Token Flow Model[END_REF] are often used to specify multiprocessor applications. Nodes in the graph, called actors, communicate with each other via tokens carried over the edges in the graph. An actor firing typically models a data transformation or some other activity and it consumes tokens from its inputs and produces tokens on its outputs. An actor may have an edge to itself (self-edge), modeling the state saving of an actor. We use stepwise refinement of the application SDF model to include mapping decisions and to model the effects of architecture details such as buffer sizes. During this refinement, actors are annotated with appropriate execution times. The result is a combined SDF graph of the application and the architecture with predictable behavior wrt timing, memory usage etc. See [START_REF] Poplavko | Task-level timing models for guaranteed performance in multiprocessor networks-on-chip[END_REF] for an example of such a flow. The mapping of data structures onto memories is one of the decisions that should be taken into account in this flow. To be able to reason about the timing properties of this mapping decision, we need a model of the memory accesses to the remote memory. Such a model is presented in Sec. 3. The communication between the remote memory and a local actor is handled by the communication assist (CA). Its role is to provide (pre)fetching of data from a remote memory in a transparent manner to a programmer. Support for prefetching is important as it allows hiding of large delays experienced when data is fetched over the network. The CA cannot be ignored when we want to build a predictable system with acceptable timing. Therefore, we need to refine the memory access model with an SDF model, presented in Sec. 4, of the (pre)fetching functionality of the CAs for accessing data in a remote tile memory. Timing annotations are omitted because they are application and architecture specific.

Memory access model

Assume an actor A with a single input i, a single output o and a self-edge for its state. Furthermore, assume that input and state are stored in remote memory, and output in local memory. The following approach can be used to model this mapping decision (other mappings can be handled similarly). The basic idea is that the remote tile memory is modeled through a separate actor M. An actor can send a token to M to request a read or write of data stored in memory M. On its turn, M returns the requested data elements to the requesting actor. A BDF model based on this idea is shown in Fig. 1. The state of A stored in the remote tile memory is modeled via the self-edge on actor M. The input data for A, also stored in the remote tile memory, is modeled via the loop going through the switch S 1 , the select S 2 and the actor M. The switch S 1 and select S 2 are used to keep the existing input token (both control tokens true) or to read a new input token from i into the remote tile memory (both control tokens false). This approach allows for (pre)fetching of data elements to be incorporated later. The functionality of actor A is split over two actors A 1 and A 2 which allows tighter bounds on the time at which tokens are consumed/produced because A 2 and M can operate in parallel. When actor A 1 is executed, it reads the data elements it requested from the remote tile memory into the local memory. The local tile memory is modeled by the edges from A 1 to A 2 and from A 2 to switch S 3 . A 1 simultaneously sends a new request to the remote tile memory to read and/or write data. It further outputs control tokens for S 1 and S 2 , both with the same value. As soon as A 1 finishes its firing, it hands over control to A 2 . Actor A 2 reads the local state and performs a transformation on it, which is equal to the transformation performed by the original actor A. At the end of its firing, it outputs a control token to switch S 3 . This switch is used to control the production of an output token for the original actor A on its output o. The actor A 2 indicates to the switch whether the produced data, stored in local memory, is valid or not. If it is not valid, the token is discarded; if it is valid, the token is put on output o. Actor A 2 hands back control to A 1 as soon as it has to read or write data that is not stored in the local tile memory. Remote memory tiles will be shared among many processing tiles. To get a predictable system, each processing tile must get guarantees on the response time of the remote memory. This can be realized by using a TDMA scheme to control access to the remote memory [START_REF] Bekooij | Predictable multiprocessor system design[END_REF]. Using such a scheme, different processing tiles using the same remote memory can be considered independently. For each actor A whose data is mapped to a remote memory we can use the model shown in Fig. 1 (or variants of it for different mapping decisions). The sharing of the remote memory is taken into account via the timing behavior of actor M (memory).

Prefetching model

(Pre)fetching functionality is implemented in the CAs in our architecture template. Consider the ith firing of actors A 1 and A 2 in the memory access model of Fig. 1,called A 1,i and A 2,i in the remainder. Actor firing A 1,i produces data for firing A 2,i and it requests data from the remote memory that is needed for firing i + 1 of A 2 . The local CA sends this request to the remote CA. On its turn, the remote CA will return the requested data. Next, the local CA has to copy the data into the local tile memory. However, it might be that not all requested data can be stored in the local memory when firing A 2,i is being executed (and thus part of the local memory is still occupied). For that reason, the local CA might have to break the request to the remote CA into two steps. First, the local CA requests and receives the data

A A 1,i CA l,1 CA l,2 CA l,3 CA l,4
CAr,1 CAr,2 that can be prefetched during firing A 2,i . Next, it fetches the data that could not be stored in the local memory. An SDF model for the behavior of the CAs is shown in Fig. 2. The various firings of A 1 and A 2 are turned into separate actors. The actors CA l,1 , CA r,1 and CA l,2 model the prefetching of data and the actors CA l,3 , CA r,2 and CA l,4 model the fetching of data. These last three actors can be omitted if all data can be prefetched. Note that the remote tile memory actor M has been abstracted away. Its (timing) behavior is included in the CA r actors. It is interesting to observe that the untimed (pre)fetching model of Fig. 2 is independent of the prefetching strategy. Prefetching strategies only influence the execution time annotations of the model.

Results

We used our approach to determine the communication bandwidth and network interface buffer sizes that must be allocated to guarantee the performance of a motion compensator in an H.263 decoder. For this we used, besides the models presented here, an SDF model of the network. The resulting design space is shown in Fig. 3. The experiment shows that the number of frames per second is not influenced by the allocated bandwidth (which is always sufficient), but that the network interface buffers need to be large (64 elements) to obtain the maximal throughput.

Figure 1 .

 1 Figure 1. BDF model for remote memory accesses to state and input data.

Figure 2 .

 2 Figure 2. SDF model for (pre)fetching.

Figure 3 .

 3 Figure 3. H.263 design space.

Proceedings of the Design, Automation and Test in Europe Conference and Exhibition (DATE'05) 1530-1591/05 $ 20.00 IEEE


Clifford W Fong Eigenenergy
email: cwfong@internode.on.net

Free radicals in chemotherapy induced cytotoxicity and oxidative stress in triple negative breast and ovarian cancers under hypoxic and normoxic conditions

Keywords: triple negative breast cancer, ovarian cancer, cytotoxicity, hypoxia, anoxia, normoxia, free radicals, oxidative stress, electron affinity, BRCA1, HIF-1α, VEGF, quantum mechanics

Free radicals in chemotherapy induced cytotoxicity and oxidative stress in triple negative breast and ovarian cancers under hypoxic and normoxic conditions

Introduction

There are two main approaches towards targeting hypoxia in cancer chemotherapy: bioreductive prodrugs (such as tirapazamine, and quinones) and inhibitors of molecular targets upon which hypoxic cell survival depends, such as the hypoxia-inducible factor-1 (HIF-1) or Src tyrosine kinase or the vascular endothelial growth factor family VEGF. [1][START_REF] Kappus | Overview of enzyme systems involved in bio-reduction of drugs and in redox cycling[END_REF][START_REF] Brown | Exploiting tumour hypoxia in cancer treatment[END_REF][START_REF] Wa Denny | Prospects for hypoxia-activated anticancer drugs[END_REF][Wilson 2011, [START_REF] Kappus | Overview of enzyme systems involved in bio-reduction of drugs and in redox cycling[END_REF][START_REF] Brown | Exploiting tumour hypoxia in cancer treatment[END_REF][START_REF] Wa Denny | Prospects for hypoxia-activated anticancer drugs[END_REF] However a third approach which is similar to the bioreduction of prodrugs, can involve bioreduction of many anti-cancer drugs followed by direct cytotoxicity or by the formation of reactive oxygen species (ROS) which subsequently cause oxidative stress (OS) leading to cellular damage. Extensive evidence supports involvement of electron transfer (ET), ROS and OS in the mechanism of many anticancer drugs. These free radical ET agents function catalytically in redox cycling with formation of ROS from oxygen. These ET agents include aliphatic and aromatic N-oxides, quinones (or phenolic precursors), metal complexes, aromatic nitro compounds (or reduced hydroxylamine and nitroso derivatives), and conjugated imines (or iminium species). It is known that cancer cells may be characterized by a reduced intracellular environment and high levels of antioxidants with weakly bound electrons. [1,[START_REF] Kovacic | Unifying mechanism for anticancer agents involving electron transfer and oxidative stress: clinical implications[END_REF][START_REF] Sainz | Radical Decisions in Cancer: Redox Control of Cell Growth and Death[END_REF][START_REF] Neesse | Electron Transfer-Based Compounds: A Novel Weapon in the Cancer Battlespace?[END_REF][Wilson 2011, [START_REF] Kovacic | Unifying mechanism for anticancer agents involving electron transfer and oxidative stress: clinical implications[END_REF][START_REF] Sainz | Radical Decisions in Cancer: Redox Control of Cell Growth and Death[END_REF], Neese 2016] OS is a normal function in all cells. ROS are produced in a controlled manner in normal cells and regulate various cellular functions including transcriptional regulation and signal transduction [reviewed in [START_REF] Jv Moreira | The Redox Status of Cancer Cells Supports Mechanisms behind the Warburg Effect[END_REF] Moreira 2016, [START_REF] Muz | The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy[END_REF] Muz 2015, [START_REF] Valko | Free radicals, metals and antioxidants in oxidative stress-induced cancer[END_REF] Valko 2006, [START_REF] Kwee | A Paradoxical Chemoresistance and Tumor Suppressive Role of Antioxidant in Solid Cancer Cells: A Strange Case of Dr. Jekyll and Mr. Hyde[END_REF] Kwee 2014, [START_REF] Kovacic | Broad overview of oxidative stress and its complications in human health[END_REF] [START_REF] Kovacic | Broad overview of oxidative stress and its complications in human health[END_REF]. Uncontrolled production of ROS causes OS that can result in DNA damage and impaired cellular functions leading to various human diseases including cancer. OS occurs when excessive production of ROS overwhelms the antioxidant defence system of the body. Cellular targets of OS include DNA, lipids, proteins, damage and modulation of kinase signalling.

Bioreduction of anti-cancer drugs can be induced by a number of enzymic systems. [1][START_REF] Kappus | Overview of enzyme systems involved in bio-reduction of drugs and in redox cycling[END_REF][START_REF] Brown | Exploiting tumour hypoxia in cancer treatment[END_REF][START_REF] Wa Denny | Prospects for hypoxia-activated anticancer drugs[END_REF][Wilson 2011, [START_REF] Kappus | Overview of enzyme systems involved in bio-reduction of drugs and in redox cycling[END_REF][START_REF] Brown | Exploiting tumour hypoxia in cancer treatment[END_REF][START_REF] Wa Denny | Prospects for hypoxia-activated anticancer drugs[END_REF] with mitochondrial processes having a particularly important role. It is thought that most of the one-electron reductases responsible for the redox cycling and hypoxic selectivity of drugs are the NAD(P)H-dependent flavoproteins which have low substrate affinities. Another group of two-electron reductases which are not inhibited by oxygen are believed to catalyse hydride (H -) transfer from NAD(P)H. [1,[START_REF] Kappus | Overview of enzyme systems involved in bio-reduction of drugs and in redox cycling[END_REF][Wilson 2011, [START_REF] Kappus | Overview of enzyme systems involved in bio-reduction of drugs and in redox cycling[END_REF] A recent study comparing the redox properties of cancer and normal cells is pertinent to the bioreduction of anti-cancer drugs: the average ATP concentration over the cell cycle is higher and the intracellular acidity pH i is globally more acidic in normal proliferating cells than in cancer cells. The NAD + /NADH and NADP + /NADPH redox ratios are, respectively, five times and ten times higher in cancer cells compared to the normal cell population. A drastic decrease of the mitochondrial membrane potential of human and mice normal and cancer cell lines is reported in cancer cell lines compared to their normal counterparts. [START_REF] Jv Moreira | The Redox Status of Cancer Cells Supports Mechanisms behind the Warburg Effect[END_REF][Moreira 2016] It is known that the oxygen level in hypoxic tumour tissues is poorer than the oxygenation of the respective normal tissues and on average it is between 1%-2% O2 and below. [START_REF] Muz | The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy[END_REF] [START_REF] Muz | The role of hypoxia in cancer progression, angiogenesis, metastasis, and resistance to therapy[END_REF] Drug-induced oxidative stress is implicated as a mechanism of toxicity in numerous tissues and organ systems. The metabolism of a drug may generate a reactive intermediate that can reduce molecular oxygen directly to generate ROS. There is extensive evidence of chemotherapy induced oxidative stress during anti-neoplastic processes. [START_REF] Deavall | Drug-Induced Oxidative Stress and Toxicity[END_REF][START_REF] Chen | Collateral damage in cancer chemotherapy: oxidative stress in nontargeted tissues[END_REF][START_REF] Ka Conklin | Chemotherapy-Associated Oxidative Stress: Impact on Chemotherapeutic Effectiveness[END_REF][START_REF] Banerjee | Drug Metabolism and Oxidative Stress: Cellular Mechanism and New Therapeutic Insights[END_REF] Many anti-cancer drugs have multiple mechanisms of action. For example Doxorubicin has three modes of action: intercalation into the DNA to prevent replication, interference with topoisomerase II which is involved in DNA replication, or by the formation of a free radical form which can generate oxidative stress in cancer cells. [14,18,19] [Chen 2007[START_REF] Marcillat | Oxidative and non-oxidative mechanisms in the inactivation of cardiac mitochondrial electron transport chain components by doxorubicin[END_REF][START_REF] Sinha | Is Metabolic Activation of Topoisomerase II Poisons Important In The Mechanism Of Cytotoxicity?[END_REF]] It has been shown that patients with advanced breast cancer subjected to chemotherapy with doxorubicin or paclitaxel presented immediate (within 1 hour) systemic oxidative stress and red blood cell oxidative injury with anemia development. Reduced antioxidant status, ie reduced glutathione levels was also observed. It has been shown that oxidative stress is an ultimate participant in the harmful systemic processes in advanced cancer patients, and treatment with chemotherapy drugs sustains these injuries. [20] [START_REF] Panis | Oxidative stress and hematological profiles of advanced breast cancer patients subjected to paclitaxel or doxorubicin chemotherapy[END_REF] Cisplatin, a known radiosensitizer, has been shown to undergo a reductive DNA damage mechanism termed dissociative electron transfer (DET) where ultrashort-lived high energy cis-Pt(NH3)2Cl• or cis-Pt(NH3)2• radicals leading to the formation of transient anions at cisplatin's binding site of DNA with subsequent DNA damage and cell death. The DET mechanism also occurs with oxaliplatin and certain halogenated aminobenzene compounds as well. [START_REF] Fong | Platinum anti-cancer drugs: Free radical mechanism of Pt-DNA adduct formation and anti-neoplastic effect[END_REF][START_REF] Berndtsson | Acute apoptosis by cisplatin requires induction of reactive oxygen species but is not associated with damage to nuclear DNA[END_REF][ Fong 2016] Apoptosis of cancer cells induced by the aquated forms of cisplatin crosslinking with DNA is considered the major mechanism of cisplatin's anti-cancer effect, but it has also been shown that apoptosis is more likely to be due to an 'off-target' effect, likely to involve cytoplasmic generation of ROS, than being induced by DNA damage. [START_REF] Marullo | Cisplatin Induces a Mitochondrial-ROS Response That Contributes to Cytotoxicity Depending on Mitochondrial Redox Status and Bioenergetic Functions[END_REF] [START_REF] Berndtsson | Acute apoptosis by cisplatin requires induction of reactive oxygen species but is not associated with damage to nuclear DNA[END_REF]] Exposure to cisplatin induces a mitochondrial-dependent ROS response that significantly enhances the cytotoxic effect caused by DNA damage. ROS generation is independent of the amount of cisplatin-induced DNA damage and occurs in mitochondria as a consequence of protein synthesis impairment. The cytotoxic effect of cisplatin-induced mitochondrial dysfunction varies among cells and depends on mitochondrial redox status, mitochondrial DNA integrity and bioenergetic function. [START_REF] Uslu | Free radicals dependent and independent pathways of CDDP-mediated cytotoxicity and apoptosis in ovarian tumour cell lines[END_REF] [START_REF] Marullo | Cisplatin Induces a Mitochondrial-ROS Response That Contributes to Cytotoxicity Depending on Mitochondrial Redox Status and Bioenergetic Functions[END_REF]] Cisplatin has been shown to be active by both a free radical and non free radical mechanism. [START_REF] Tassone | Loss of BRCA1 function increases the antitumor activity of cisplatin against human breast cancer xenografts in vivo[END_REF][Uslu 1995] Cisplatin induced almost complete growth inhibition of BRCA1-defectivehuman breast cancer xenografts, while BRCA1reconstituted xenografts were only partially inhibited. A significant S-and G2/M cell cycle blockade in BRCA1-defective was found as compared with parental BRCA1-reconstituted cells. [START_REF] Xue | Oxidative stress is involved in Dasatinib-induced apoptosis in rat primary hepatocytes[END_REF] [START_REF] Tassone | Loss of BRCA1 function increases the antitumor activity of cisplatin against human breast cancer xenografts in vivo[END_REF] OS plays a pivotal role in dasatinib-mediated hepatotoxicity. Dasatinib greatly increased the level of ROS in hepatocytes, reduced the intracellular glutathione content, attenuated the activity of superoxide dismutase, generated malondialdehyde, a product of lipid peroxidation, decreased the mitochondrial membrane potential, and activated nuclear factor erythroid 2-related factor 2 and mitogen-activated protein kinases related to oxidative stress and survival. [START_REF] Arora | Role of Tyrosine Kinase Inhibitors in Cancer Therapy[END_REF] [START_REF] Xue | Oxidative stress is involved in Dasatinib-induced apoptosis in rat primary hepatocytes[END_REF] In cancer chemotherapy, tyrosine kinases are an important target since they play an important role in the modulation of tumour growth factor signalling, cell proliferation and migration. Tyrosine kinase inhibitors (TKI) are a class of targeted therapy that interfere with specific cell signalling pathways and hence allow target specific therapy for selected malignancies. [START_REF] Kj Gotink | Anti-angiogenic tyrosine kinase inhibitors: what is their mechanism of action?[END_REF][START_REF] Dw Siemann | Src Signaling Interference Impairs the Dissemination of Blood-Borne Tumor Cells[END_REF][START_REF] V Saffran | Src inhibitor dasatinib reduces the metastatic phenotype of breast cancer cells[END_REF][Arora 2005, Gotnik 2010, Siemann 2012] Src is a non-receptor tyrosine kinase that is frequently over-expressed in malignancies, and increased Src activity is well known to contribute to the metastatic phenotype of tumour cells. Dasatinib is a Src inhibitor. Dasatinib has been found to significantly inhibit multiple cell functions critical to the successful metastatic dissemination of 4T1 breast cancer cells. Dasatinib treatment inhibited 4T1 tumour cell-induced angiogenesis by up to 60%. The results suggest that Dasatinib may be useful in the reduction of breast cancer metastasis. [START_REF] Parikh | The vascular endothelial growth factor family and its receptors[END_REF][Saffran 2011] VEGF is secreted by all almost all solid tumours and tumour-associated stroma in response to hypoxia. It is highly specific for vascular endothelium and regulates both vascular proliferation and permeability. Excessive expression of VEGF levels correlate with increased microvascular density, cancer recurrence, and decreased survival Many TKIs are VEGF inhibitors. [START_REF] Kerbel | Targeting the VEGF/VEGFR Pathway: Strategies for Improving Therapeutic Outcomes[END_REF][START_REF] Vera-Ramirez | Free radicals in breast carcinogenesis, breast cancer progression and cancer stem cells, Biological bases to develop oxidative-based therapies[END_REF] BRCA1 acts as a tumour suppressor and functions predominantly by maintaining genome integrity. BRCA1 is also involved in oxidative stress regulation. There is extensive evidence that BRCA1 may exert its tumour suppressive functions through oxidative stress regulation. Breast cancer cells are subject to high levels of intracellular and extracellular oxidative stress. [34, [START_REF] S Ríos-Arrabal | Involvement of free radicals in breast cancer[END_REF][START_REF] Yi | BRCA1 and Oxidative Stress[END_REF][Vera-Ramirez 2011, Ríos-Arrabal 2013, [START_REF] Yi | BRCA1 and Oxidative Stress[END_REF] It has been shown that Tempol, a stable free radical, increases the apoptotic rates of triple negative breast cancer (TNBC) MDA-MB-231 cells (which have a wild-type BRCA1), but only during co-culture with fibroblasts. BRCA1, the human tumour suppressor gene and its protein, normally functions as an endogenous antioxidant, so helping prevents the onset of hereditary breast cancers. The loss of BRCA1 functionality (common in sporadic breast cancers) increases hydrogen peroxide generation in both epithelial breast cancer cells and neighbouring stromal fibroblasts, and promotes the onset of a reactive glycolytic stroma, with increased monocarboxylate transporter 4 and decreased caveolin-1expression. These glycolytic cancerassociated fibroblasts in turn provide mitochondrial fuels (such as L-lactate) to epithelial cancer cells, to burn via oxidative mitochondrial metabolism. Cancer cells produce high levels of ROS, which promotes cancer mutagenesis. By acting on cells producing ROS in the local microenvironment, Tempol antioxidant therapy appears to be synthetically lethal with a BRCA1deficiency in TNBC cells. [START_REF] Ue Martinez-Outschoorn | BRCA1 mutations drive oxidative stress and glycolysis in the tumor microenvironment. Implications for breast cancer prevention with antioxidant therapies[END_REF][START_REF] Fong | The role of free radicals in the effectiveness of anti-cancer chemotherapy in hypoxic ovarian cells and tumours[END_REF][START_REF] Fong | Role of stable free radicals in conjugated antioxidant and cytotoxicity treatment of triple negative breast cancer[END_REF][Martinez-Outschoorn 2012, Fong 2018] Germline mutations in the breast cancer susceptibility gene (BRCA1) are strongly linked to familial breast and ovarian cancers. It is known that a smaller proportion of BRCA mutations are not hereditary in origin, but are somatic or sporadic in origin. BRCA1 mutations occur in about 18% of ovarian cancers, 13% germline and 5% somatic mutations. [START_REF] Kp Pennington | Germline and somatic mutations in homologous recombination genes predict platinum response and survival in ovarian, fallopian tube, and peritoneal carcinomas[END_REF][Pennington 2014] BRCA1 mutation carriers are only predisposed to breast and ovarian tumours. [START_REF] Pa Futreal | BRCA1 mutations in primary breast and ovarian carcinomas[END_REF][START_REF] Li | Chemopreventive Effects of ROS Targeting in a Murine Model of BRCA1-Deficient Breast Cancer[END_REF][START_REF] Celik | Relationship of Breast Cancer with Ovarian Cancer, A Concise Review of Molecular Pathology of Breast Cancer[END_REF][Futreal 1994, Li 2016, Celik 2015] BRCA1 is involved in ROS production and in the response to oxidative stress, exerting antioxidant activity by inducing the expression of antioxidant enzymes. It is a multifunctional protein involved in numerous cell processes, including cell cycle control, maintenance of genetic stability, DNA damage repair, apoptosis, and the transcription of different genes. Cancer cells with BRCA1 mutations suffer from genomic instability and increased DNA lesions. [START_REF] S Ríos-Arrabal | Involvement of free radicals in breast cancer[END_REF][START_REF] Yi | BRCA1 and Oxidative Stress[END_REF][START_REF] Celik | Relationship of Breast Cancer with Ovarian Cancer, A Concise Review of Molecular Pathology of Breast Cancer[END_REF][Rios-Arrabal 2013, Yi 2014, Celik 2015] Modifications to BRCA1 induced by oxidative stress influence nuclear events that can weaken DNA repair response. It is thought that antioxidant modalities may be a chemo-preventative strategy for familial breast cancers. [START_REF] Bl Gilmore | Molecular Analysis of BRCA1 in Human Breast Cancer Cells Under Oxidative Stress[END_REF][START_REF] Li | Chemopreventive Effects of ROS Targeting in a Murine Model of BRCA1-Deficient Breast Cancer[END_REF][START_REF] Yi | BRCA1 and Oxidative Stress[END_REF][Gilmore 2017, Li 2016, [START_REF] Yi | BRCA1 and Oxidative Stress[END_REF] There is a potential for chemotherapeutic agents to induce somatic changes to the BRCA genes, particularly if highly reactive free radical species are involved in the anti-cancer processes. [Banerjee 2016[START_REF] Ka Conklin | Chemotherapy-Associated Oxidative Stress: Impact on Chemotherapeutic Effectiveness[END_REF] ] Some sporadic ovarian cancers have the same pathological traits of BRCA mutation-associated cases, but in the absence of a germline BRCA mutation, described as 'BRCAness'. BRCA1 and BRCA2 germline mutations were identified in 9% and 8% of the cases, whereas somatic BRCA mutations occur in approximately 5%-7% of ovarian cancer cases. [START_REF] Bl Gilmore | Molecular Analysis of BRCA1 in Human Breast Cancer Cells Under Oxidative Stress[END_REF][START_REF] Moschetta | BRCA somatic mutations and epigenetic BRCA modifications in serous ovarian cancer[END_REF][START_REF] Alsop | BRCA Mutation Frequency and Patterns of Treatment Response in BRCA Mutation-Positive Women With Ovarian Cancer: A Report From the Australian Ovarian Cancer Study Group[END_REF][Gilmore 2017, Moschetta 2016, [START_REF] Alsop | BRCA Mutation Frequency and Patterns of Treatment Response in BRCA Mutation-Positive Women With Ovarian Cancer: A Report From the Australian Ovarian Cancer Study Group[END_REF] BRCA1 binds and stabilizes the hypoxia-inducible factor-1α (HIF-1α) and activates its target gene vascular endothelial growth factor (VEGF). Under hypoxic condition, BRCA1 stimulates VEGF promoter activity along with HIF-1α. [START_REF] Hj Kang | BRCA1 Plays a Role in the Hypoxic Response by Regulating HIF-1α Stability and by Modulating Vascular Endothelial Growth Factor Expression[END_REF][Kang 2016] HIF-1 is a protein with DNA binding activity. It is composed of two subunits: HIF-1 and HIF-1. Among the first responses at the onset of tumour hypoxia is an increase in the protein levels of HIF-1. HIF-1 helps normal tissues as well as tumors to survive under hypoxic conditions, and severe hypoxia is usually found in solid tumors. HIF-1 is a transcription factor that turns on genes needed for survival under hypoxic conditions. More than 40 target genes have been found to be regulated by HIF-1. Because hypoxia in the tumour microenvironment is a driving force in breast cancer metastasis, it has been found that cytotoxic chemotherapy (such as paclitaxel or gemcitabine) combined with drugs that inhibit hypoxia-inducible factors (such as acriflavine or digoxin) can improve outcomes for women with TNBC. [START_REF] Gl Semenza | The hypoxic tumor microenvironment: A driving force for breast cancer progression[END_REF][Semenza 2015] Increased HIF-1α expression is known to contribute to mitochondrial activity and ROS formation during hypoxia. High ROS concentrations generated from the mitochondria have been shown to stabilize HIF-1α. ROS may be also produced in the cytosol, derived from NADPH oxidases. [START_REF] Ns Chandel | Reactive oxygen species generated at mitochondrial complex III stabilize hypoxiainducible factor-1alpha during hypoxia: a mechanism of O2 sensing[END_REF][START_REF] Chang | Stabilization of hypoxia-inducible factor-1α by prostacyclin under prolonged hypoxia via reducing reactive oxygen species level in endothelial cells[END_REF][Chandel 2000, [START_REF] Chang | Stabilization of hypoxia-inducible factor-1α by prostacyclin under prolonged hypoxia via reducing reactive oxygen species level in endothelial cells[END_REF]] HIF-1α is not expressed during normoxia.

Study objectives

(a) To examine whether the free radical species of a series of anti-cancer drugs can be involved in breast and ovarian cancer cell cytotoxicity under hypoxic and normoxic conditions (b) To examine chemotherapy induced cytotoxicity and oxidative stress in breast and ovarian cancer treatment and mutations of the BRCA genes under hypoxic or anoxic conditions

Results

The drug cytotoxicity data for the human breast cancer cell line MDA-MB-231, under normoxia and hypoxia (0.1% oxygen) conditions (Table 1) [START_REF] Ahmadi | Hypoxia modulates the activity of a series of clinically approved tyrosine kinase inhibitors[END_REF][Ahmadi 2014] and the human ovarian cancer cell line A2780, under normoxia (20% O 2 ), and hypoxia (1% O 2 ) anoxia 0.1% oxygen conditions (Table 2, drugs in the free radical form) [START_REF] Strese | Effects of hypoxia on human cancer cell line chemosensitivity[END_REF][ [START_REF] Strese | Effects of hypoxia on human cancer cell line chemosensitivity[END_REF]] have been analysed using the general equation (1).

Equation 1 has been shown to apply to the transport and anti-cancer and metabolic efficacy of various drugs. The model, equation 1, is based on establishing linear free energy relationships between the four drug properties and various biological processes. Equation 1 has been previously applied to passive and facilitated diffusion of a wide range of drugs crossing the blood brain barrier, the active competitive transport of tyrosine kinase inhibitors by the hOCT3, OATP1A2 and OCT1 transporters, and cyclin-dependent kinase inhibitors and HIV-1 protease inhibitors. The model also applies to PARP inhibitors, the anti-bacterial and anti-malarial properties of fluoroquinolones, and active organic anion transporter drug membrane transport, and some competitive statin-CYP enzyme binding processes. There is strong independent evidence from the literature that ΔG desolvation , ΔG lipophilicity , the dipole moment and molecular volume are good inherent indicators of the transport or binding ability of drugs. [START_REF] Fong | The extravascular penetration of tirapazamine into tumours: a predictive model of the transport and efficacy of hypoxia specific cytotoxic analogues and the potential use of cucurbiturils to facilitate delivery[END_REF][59][60][START_REF] Fong | The effect of desolvation on the binding of inhibitors to HIV-1 protease and cyclin-dependent kinases: Causes of resistance[END_REF][START_REF] Fong | Predicting PARP inhibitory activity -A novel quantum mechanical based model[END_REF][START_REF] Fong | A novel predictive model for the anti-bacterial, anti-malarial and hERG cardiac QT prolongation properties of fluoroquinolones[END_REF][START_REF] Fong | Statins in therapy: Cellular transport, side effects, drug-drug interactions and cytotoxicity -the unrecognized role of lactones[END_REF][START_REF] Fong | Physiology of ionophore transport of potassium and sodium ions across cell membranes: Valinomycin and 18-Crown-6 Ether[END_REF][START_REF] Fong | Statins in therapy: Understanding their hydrophilicity, lipophilicity, binding to 3-hydroxy-3-methylglutaryl-CoA reductase, ability to cross the blood brain barrier and metabolic stability based on electrostatic molecular orbital studies[END_REF][START_REF] Fong | The effect of lipophilic modifications to dasatinib on ovarian cancer cytotoxicity proliferation and anti-angiogenesis[END_REF][ Fong 2014-17].

Equation 1:

Transport or Binding = ΔG desolv,CDS + ΔG lipo,CDS + Dipole Moment + Molecular Volume or Ionization Potential or Electron Affinity

Equation 1 uses the free energy of water desolvation (ΔG desolv,CDS ) and the lipophilicity free energy (ΔG lipo,CDS ) where CDS represents the non-electrostatic first solvation shell solvent properties. CDS may be a better approximation of the cybotactic environment around the drug approaching or within the protein receptor pocket, or the cell membrane surface or the surface of a drug transporter, than the bulk water environment outside the receptor pocket or cell membrane surface. The CDS includes dispersion, cavitation, and covalent components of hydrogen bonding, hydrophobic effects. Desolvation of water from the drug (ΔG desolv,CDS ) before binding in the receptor pocket is required, and hydrophobic interactions between the drug and protein (ΔG lipo,CDS ) is a positive contribution to binding. ΔG lipo,CDS is calculated from the solvation energy in n-octane. In some biological processes, where oxidation or reduction may be occurring, and the influence of molecular volume is small, the ionization potential or reduction potential (adiabatic electron affinity) has been included in place of the molecular volume. In other processes, the influence of some of the independent variables is small and can be eliminated to focus on the major determinants of biological activity.

We have recently used this model to develop a predictive model of the transport and efficacy of hypoxia specific cytotoxic analogues of tirapazmine and the effect on the extravascular penetration of tirapazamine into tumours. [START_REF] Fong | The extravascular penetration of tirapazamine into tumours: a predictive model of the transport and efficacy of hypoxia specific cytotoxic analogues and the potential use of cucurbiturils to facilitate delivery[END_REF][Fong 2017] It was found that the multiparameter model of the diffusion, antiproliferative assays IC 50 and aerobic and hypoxic clonogenic assays for a wide range of neutral and radical anion forms of tirapazamine (TPZ) analogues showed: (a) extravascular diffusion is governed by the desolvation, lipophilicity, dipole moment and molecular volume, similar to passive and facilitated permeation through the blood brain barrier and other cellular membranes, (b) hypoxic assay properties of the TPZ analogues showed dependencies on the electron affinity, as well as lipophilicity and dipole moment and desolvation, similar to other biological processes involving permeation of cellular membranes, including nuclear membranes, (c) aerobic assay properties were dependent on the almost exclusively on the electron affinity, consistent with electron transfer involving free radicals being the dominant species. For the TNBC results, under normoxia eq 2(b) & hypoxia 3(b), the coefficients for the ratios {ΔG desolv,CDS : ΔG lipo,CDS } & {ΔG lipo,CDS : AEA} for eq 2(b) are 1:2 & 2:1. For eq 3(b) the ratios are 1:2.2 & 2.2:1.5. These ratios show that water desolvation and lipophilicity are relatively of equal importance, but the AEA become more important under hypoxia, consistent with a greater free radical mechanism under hypoxic conditions. The partial dependence on desolvation and lipophilicity points to some drug-target binding interaction, and/or some drug-cell membrane transport interaction.

For the ovarian cancer cells, comparison of anoxia eq 4(b) and hypoxia 5(b) show that the AEA is the statistically dominant factor, with water desolvation and lipophilicity being insignificant. It is noted that eq 4(b) and 5(b) are actually IC 50 ratios of anoxia or hypoxia relative to normoxia conditions. Eq 6(b) suggests that free radical species also play a role during cytotoxicity under normoxia, as well as anoxia and hypoxia, though much reduced.

The data in the equations described above refer to cellular cytotoxicity but the molecular target(s) in these processes are unknown. However, the available literature on the effect of chemotherapy on TNBC and ovarian cancer, and the known relationship between TNBC and ovarian cancer can be indicative of the likely target(s).

The literature described in the introduction on anti-cancer properties of TNBC and ovarian cancers points to a strong linkage between the two cancers with free radicals most likely being involved, particularly under hypoxic or anoxic conditions.

By acting on cells producing ROS in the local microenvironment, Tempol (a stable free radical) antioxidant therapy appears to be synthetically lethal with a BRCA1-deficiency in TNBC cells. [START_REF] Ue Martinez-Outschoorn | BRCA1 mutations drive oxidative stress and glycolysis in the tumor microenvironment. Implications for breast cancer prevention with antioxidant therapies[END_REF][START_REF] Fong | The role of free radicals in the effectiveness of anti-cancer chemotherapy in hypoxic ovarian cells and tumours[END_REF][START_REF] Fong | Role of stable free radicals in conjugated antioxidant and cytotoxicity treatment of triple negative breast cancer[END_REF] BRCA1 binds and stabilizes the hypoxia-inducible factor-1α (HIF-1α) and activates its target gene vascular endothelial growth factor (VEGF). VEGF is secreted by all almost all solid tumours and tumour-associated stroma in response to hypoxia. Under hypoxic condition, BRCA1 stimulates VEGF promoter activity along with HIF-1α. [START_REF] Hj Kang | BRCA1 Plays a Role in the Hypoxic Response by Regulating HIF-1α Stability and by Modulating Vascular Endothelial Growth Factor Expression[END_REF][Kang 2016] Increased HIF-1α expression is known to contribute to mitochondrial activity and ROS formation during hypoxia. High ROS concentrations generated from the mitochondria have been shown to stabilize HIF-1α. ROS may be also produced in the cytosol, derived from NADPH oxidases. [START_REF] Ns Chandel | Reactive oxygen species generated at mitochondrial complex III stabilize hypoxiainducible factor-1alpha during hypoxia: a mechanism of O2 sensing[END_REF][START_REF] Chang | Stabilization of hypoxia-inducible factor-1α by prostacyclin under prolonged hypoxia via reducing reactive oxygen species level in endothelial cells[END_REF][Chandel 2000, [START_REF] Chang | Stabilization of hypoxia-inducible factor-1α by prostacyclin under prolonged hypoxia via reducing reactive oxygen species level in endothelial cells[END_REF]] HIF-1α is not expressed in normoxia.

The TNBC human breast cancer cell line MDA-MB-231 and the ovarian cancer cell line A2780 used in this study both have a wild type BRCA1 gene. [START_REF] Ue Martinez-Outschoorn | BRCA1 mutations drive oxidative stress and glycolysis in the tumor microenvironment. Implications for breast cancer prevention with antioxidant therapies[END_REF][START_REF] Stordal | BRCA1/2 mutation analysis in 41 ovarian cell lines reveals only one functionally deleterious BRCA1 mutation[END_REF][Martinez-Outschoorn 2012, Stordahl 2013,] The breast cancer drugs used in this study are very varied and come from quite different drug classes. They include a wide range of tyrosine kinase inhibitors, anti-metabolite pyrimidine analogue (5 Fluorouracil, Gemcitabine), proteasome inhibitor (Bortezomib), platinum compounds (Cisplatin), cardiac glycosides (Digitoxin, Digoxin), anthracyclines and topoisomerase II inhibitors (Doxorubicin, Irinotecan, Topotecan), quinone antibiotics (Mitomycin C), mitosis inhibitors or taxanes (Docetaxel, Etoposide), antiseptic (Acriflavine), alkylating mustard analogue (Melphalan), oral macrolide, m-TOR inhibitor (Rapamycin), bioreductive pro-drug (Tirapazamine), vinca alkaloids (Vinblastin). It is possible that some of these drugs used in this study exhibit multiple mechanisms (such as those known for Doxorubicin, Cisplatin etc) but a common free radical / oxidative stress mechanism can provide a generic mechanism for the observed cytotoxicity, especially since many of the investigated drugs are independently known to use free radicals to exert their anti-cancer effect.

A plausible hypothesis that can explain the results for the TNBC and ovarian cancer cells is that free radicals are involved in an oxidative stress environment where HIF-1α expression occurs in hypoxic or anoxic conditions, and may involve BRCA1 mutations and VEGF. This hypothesis relies on known literature studies regarding the possible roles of BRCA1, HIF-1α and VEGF.

A proposed mechanism is: Cellular target 1 or 2 could be BRCA1/HIF-1α or VEGF.

Conclusions

An analysis of the cytotoxicity data for a wide range of anti-cancer drugs applied to triple negative breast cancer (TNBC) cells and ovarian cancer cells under normoxic, hypoxic and anoxic conditions has shown that free radical forms of the drugs are involved. This finding is consistent with the known involvement of oxidative stress in the TNBC and ovarian cancer cells. A mechanism to explain the formation of these drug free radicals and how they can be involved in oxidative stress is proposed.

A hypothesis that might explain the known link between TNBC and ovarian cancer is proposed which involves involvement of free radicals interacting with the BRCA1/HIF-1α complex or VEGF under hypoxic or anoxic conditions.

  [Deavall 2012[START_REF] Chen | Collateral damage in cancer chemotherapy: oxidative stress in nontargeted tissues[END_REF][START_REF] Ka Conklin | Chemotherapy-Associated Oxidative Stress: Impact on Chemotherapeutic Effectiveness[END_REF], Banerjee 2016] Patients with breast cancer treated with Doxorubicin and Cyclophosphamide chemotherapy presented with oxidative stress before, during, and after treatment, as well as showing increased genotoxic damage in all stages of treatment.[17][Junior 2015]

  [START_REF] Parikh | The vascular endothelial growth factor family and its receptors[END_REF],[START_REF] Kerbel | Targeting the VEGF/VEGFR Pathway: Strategies for Improving Therapeutic Outcomes[END_REF]].There is extensive evidence that OS plays a major role in breast cancer.[34][START_REF] S Ríos-Arrabal | Involvement of free radicals in breast cancer[END_REF][START_REF] Bl Gilmore | Molecular Analysis of BRCA1 in Human Breast Cancer Cells Under Oxidative Stress[END_REF][START_REF] Li | Chemopreventive Effects of ROS Targeting in a Murine Model of BRCA1-Deficient Breast Cancer[END_REF][Vera-Ramirez 2011, Ríos-Arrabal 2013, Gilmore 2017,[START_REF] Li | Chemopreventive Effects of ROS Targeting in a Murine Model of BRCA1-Deficient Breast Cancer[END_REF]] OS also has an important role in the pathogenesis, neoangiogenesis, and dissemination of local or distant ovarian cancer, as it induces phenotypic modifications of tumour cells by cross talk between tumour cells and the surrounding stroma. OS has a major role in the pathogenesis and chemotherapy of ovarian cancer.[START_REF] Saed | Updates of the role of oxidative stress in the pathogenesis of ovarian cancer[END_REF][START_REF] Senthil | Evidence of oxidative stress in the circulation of ovarian cancer patients[END_REF][START_REF] Bandebuche | Oxidative Stress and Antioxidant Status in Patients of Ovarian Cancer[END_REF][START_REF] Sa Bukhari | Oxidative stress-induced DNA damage and homocysteine accumulation may be involved in ovarian cancer progression in both young and old patients[END_REF][START_REF] Pylvas | Oxidative stress induced antioxidant enzyme expression is an early phenomenon in ovarian carcinogenesis[END_REF][Saed 2017, Senthil 2004, Bandebuche 2011, Bukhari 2016, Pylvas 2010]

( a )

 a Human Breast Cancer cell line MDA-MB-231, under normoxia (~20% oxygen) and hypoxia 0.1% oxygen conditions[START_REF] Ahmadi | Hypoxia modulates the activity of a series of clinically approved tyrosine kinase inhibitors[END_REF][START_REF] Ahmadi | Hypoxia modulates the activity of a series of clinically approved tyrosine kinase inhibitors[END_REF] Where the relevant pKa values indicate that significant concentrations of the protonated species exist at physiological pH, these species have also been included in the analyses along with the neutral species of the drugs. AEA values have been normalised (multiplied by a factor of 5 to allow direct comparison of the magnitude of the various coefficients in the following equations).Normoxia analysis yields: IC50 (μM) Excluding Imatinib as an outlier 18 drugs including 5-Fluorouracil, Doxorubicin, Vinblastin, Dasatinib, DasatinibH + , Vandetinib, VandetinibH + , Gefitinib, GefitinibH + , Masatinib, MasatinibH + , Nilotinib, NilotinibH + , Sunitinib, SunitinibH + , Sorafenib, Tirapazamine, as drug and drugH + species (excluded ErlotinibH + and ImatinibH + ) Equation 2(a) IC 50 = -0.56ΔG desolv,CDS + 0.99ΔG lipo,CDS + 0.03Dipole Moment -0.58Adiabatic Electron Affinity + 27.54 Where R 2 = 0.44, SEE = 4.27, SE(ΔG desolvCDS ) = 0.31, SE(ΔG lipoCDS ) = 0.38, SE(Dipole Moment) = 0.06, SE(AEA) = 0.40, F=2.53, Significance=0.091Equation 2(b) IC 50 = -0.55ΔG desolv,CDS + 0.92ΔG lipo,CDS -0.59Adiabatic Electron Affinity + 27.67 Where R 2 = 0.43, SEE = 4.15, SE(ΔG desolvCDS ) = 0.30, SE(ΔG lipoCDS ) = 0.34, SE(AEA) = 0.38, F=3.49, Significance=0.044 Hypoxia analysis yields: IC 50 (μM) Excluding Imatinib as an outlier 18 drugs Equation 3(a) IC 50 = -0.98ΔG desolv,CDS + 2.24ΔG lipo,CDS + 0.04Dipole Moment -1.49Adiabatic Electron Affinity + 56.44 Where R 2 = 0.58, SEE = 7.22, SE(ΔG desolvCDS ) = 0.53, SE(ΔG lipoCDS ) = 0.64, SE(Dipole Moment) = 0.11, SE(AEA) = 0.67, F=4.40, Significance=0.018 Equation 3(b) IC 50 = -0.97ΔG desolv,CDS + 2.17ΔG lipo,CDS -1.50Adiabatic Electron Affinity + 56.58 Where R 2 = 0.57, SEE = 6.99, SE(ΔG desolvCDS ) = 0.41, SE(ΔG lipoCDS ) = 0.57, SE(AEA) = 0.65, F=6.25, Significance=0.006 (b) Human Ovarian Cancer cell line A2780, under normoxia (20% O 2 ), and hypoxia (1% O 2 ) anoxia 0.1% oxygen conditions: 17 drugs in the free radical form with their cytotoxicity ratios (Ranox = anoxic IC 50 /normoxic IC 50 and Rhypox = hypoxic IC 50 /normoxic IC 50 ) and the normoxia IC 50 values taken from [57] [Strese 2013] (Drugs: 5-Fluorouracil, Bortezomib, Cisplatinum, Digitoxin, Digoxin, Docetaxel, Doxorubicin, Etoposide, Irinotecan, Melphalan, Mitomycin C, Rapamycin, Sorafenib, Topotecan, Tirapazamine, Vincristine) AEA values have been normalised (multiplied by a factor of 5 to allow direct comparison of the magnitude of the various coefficients in the following equations). R anox Anoxia analysis yields: Excluding Vincristine as an outlier Equation 4(a) R anox = -0.037ΔG desolv,CDS + 0.029ΔG lipo,CDS + 0.038Dipole Moment -0.079Adiabatic Electron Affinity + 1.142 Where R 2 = 0.656, SEE = 0.690, SE(ΔG desolvCDS ) = 0.059, SE(ΔG lipoCDS ) = 0.064, SE(Dipole Moment) = 0.014, SE(AEA) = 0.050, F=5.24, Significance=0.013 Equation 4(b) Excluding Vincristine as an outlier R anox = -0.118Adiabatic Electron Affinity + 2.540 Where R 2 = 0.321, SEE = 0.701, SE(AEA) = 0.008, F=6.14, Significance=0.027 R hypox Hypoxia analysis yields: Excluding Vincristine as an outlier Equation 5(a) R hypox = 0.073ΔG desolv,CDS -0.063ΔG lipo,CDS -0.003Dipole Moment -0.130Adiabatic Electron Affinity + 2.613 Where R 2 = 0.649, SEE = 0.690, SE(ΔG desolvCDS ) = 0.036, SE(ΔG lipoCDS ) = 0.040, SE(Dipole Moment) = 0.009, SE(AEA) = 0.031, F=4.63, Significance=0.022 Equation 5(b) Excluding Vincristine as an outlier R hypox = -0.111Adiabatic Electron Affinity + 2.165 Where R 2 = 0.504, SEE = 0.450, SE(AEA) = 0.030, F=13.22, Significance=0.003 Normoxia analysis yields: Equation 6(a) Excluding Fluorouracil and Vincristine as outliers IC 50 Normoxia = 0.489ΔG desolv,CDS -2.089ΔG lipo,CDS -1.438Dipole Moment + 3.323Adiabatic Electron Affinity + 1.544 Where R 2 = 0.443, SEE = 33.500, SE(ΔG desolvCDS ) = 2.438, SE(ΔG lipoCDS ) = 3.167, SE(Dipole Moment) = 0.720, SE(AEA) = 2.438, F=2.00, Significance=0.171 Equation 6(b) Excluding Fluorouracil and Vincristine as outliers IC 50 Normoxia = 4.446Adiabatic Electron Affinity -27.109 Where R 2 = 0.214, SEE = 34.91, SE(AEA) =2.216, F=3.54, Significance=0.082 Discussion Equations 2(b) and 3(b) for TNBC and 4(b) and 5(b) for ovarian cancer cells show that the free radical forms of the various anti-cancer drugs play a role in cellular cytotoxicity under normoxic conditions but become increasing important under anoxic or hypoxic conditions.

9 ROS + cellular target 2 

 92 Drug + e• (bioreductase)  Drug• (Rate determining step) Eq 7 Drug• + cellular target 1  {cellular target 1}•  cell death (Anoxia or Hypoxia) Eq 8 Drug• + O 2  O 2 • -(+ other ROS) + Drug (Hypoxia or Normoxia) Eq {cellular target 2}•  cell death Eq 10

  ][Martinez-Outschoorn 2012, Fong 2018] BRCA1 mutation carriers are only predisposed to breast and ovarian tumours. [48,37,49][Futreal 1994, Li 2016, Celik 2015] BRCA1 mutations can be hereditary or sporadic or somatic, with the latter two possibly chemotherapy induced. [50][Moschetta 2015]

Normoxia


Paul Muller

Armin Tajalli

Mojtaba Atarodi

Yusuf Leblebici

Top-Down Design of a Low-Power Multi-Channel 2.5-Gbit/s/Channel Gated Oscillator Clock-Recovery Circuit

come

Introduction

While processor clock frequencies and throughput increase with each new technology generation, the lack of I/O bandwidth in microprocessors is an increasing limitation of the overall communication performance of computers. Short-distance communication interfaces like computer buses and LAN systems must support higher data rates to keep the pace with the evolution of processor speed. Parallel buses send a clock signal on a separate path to the receiver. Clock skew, due to unequal path length and termination impedance, is one limiting factor of the achievable data rate on printed circuit board buses. Crosstalk generated by the relatively large signal amplitude in parallel buses, as well as ringing due to impedance variations and mismatch are other limitations. Finally the high power drain of rail-to-rail output drivers for several tens of data lanes and the resulting possible ground bounce are other problems of parallel data communication interfaces.

Fig. 1: Parallel 8-bit bus versus serial communication with equivalent data rate

Serial communications offer an important increase in data rates. Low-voltage differential signaling (LVDS) alleviates crosstalk and ground bounce, while point-topoint connections reduce impedance variations. Clock skew is not limiting the data rates in short-distance serial interfaces, as the clock is not transmitted as a separate signal. Indeed, the clock information is embedded in the data stream using 8bit/10bit encoding, which guarantees a high number of data transitions (Figure 1). Short-distance optical links provide an even more robust solution to electro-magnetic coupling and bandwidth requirements. The presented clock and data recovery (CDR) solution combines with the already demonstrated pure silicon amplification front-end ([1], [START_REF] Muller | A 4-channel 2.5Gb/s/channel 66dBOhm Inductorless Transimpedance Amplifier[END_REF]) to a complete fiber-optic receiver. Mixed-signal modeling of such a system, as discussed in this paper, is a crucial step in the definition of the block-level specifications.

A multi-channel serial-link combines several serial data links side by side. Although such wide-band very-short reach multi-channel links are limited to server interconnects (e.g. InfiniBand™) today, they will certainly progress from board-to-board to chip-to-chip links, to be integrated on backplanes and microprocessor motherboards in the near future (Figure 2). Unlike in a parallel bus, the individual links are not, and do not need to be, fully synchronous.

Fig. 2: Conceptual block diagram of an integrated multi-channel photo-receiver array for data communication

The presented design methodology allows us to design a low-power multi-channel clock and data recovery circuit with a power consumption lower than 5mW/Gbit/s. To achieve this low power consumption, we do not intend to use popular PLL, DLL or phase interpolation techniques, but to implement a gated oscillator topology [START_REF] Kaeriyama | A 10Gb/s/ch 50mW 120x130µm clock and data recovery circuit[END_REF], which is used relatively rarely.

Statistical simulations show that the gated oscillator approach is a viable solution in presence of frequency and phase variations. Then, the required power consumption is estimated based on the analysis of the phase noise of the oscillator. Behavioral VHDL simulations verify the timedomain behavior of the design and finally SPICE-level simulations validate the transistor-level design. As such, the presented design methodology demonstrates the feasibility of a top-down approach based on quantifiable system specifications, as opposed to classical bottom-up design.

System-level specifications 2.1. Definition of jitter tolerance

Because of the skew between the links in a multichannel serial interface, individual synchronization of each channel is necessary. As the transmitter reference clock is used for all channels of a given transmitter, their data rates are identical. But each channel may exhibit a different delay, introducing skew between the channels. The CDR at the receive side must thus extract the phase of the incoming data of each channel.

The lowest bit error ratio (BER) is achieved when the data is sampled at the ideal sampling instant in between two data transitions, in most cases in the middle of the data eye (Figure 3). Timing jitter expresses the uncertainty of the sampling instant due to noise (random jitter) or systematic errors (deterministic jitter). In short-haul communications, the resynchronized data is transferred from the receive clock domain to the system clock domain through an elastic buffer (Figure 4), which resynchronizes the data with the system clock.

Fig. 3: Data eye diagram with optimum sampling point Fig. 4: System view of digital core with serial I/O

Tolerance to data jitter (JTOL) is usually tested by adding sinusoidal jitter at a given frequency to the data stream, which already includes channel jitter. The maximum jitter amplitude, function of jitter frequency, at which the CDR still operates at a given BER (typically 10 -12 ), is called jitter tolerance (Figure 5). Jitter amplitude is typically represented in unit intervals (UI) either peakpeak or RMS, depending on the nature of jitter. A unit interval represents the bit period of the incoming data, i.e. 1UI = 400ps.

Fig. 5: InfiniBand™ jitter tolerance specification[4]

Gated oscillator topology

Multi-channel CDRs require high jitter performance and low area and power consumption at the same time. The gated current-controlled oscillator (GCCO) topology represents a good trade-off for this application. As shown in Figure 6, a shared PLL generates the local highfrequency clock (HFCK) from a low-frequency crystal oscillator clock (LFCK). The shared PLL is based on a high-order loop filter to get good jitter performance and a current-controlled oscillator (CCO). It also delivers a copy of its control current I C to the matched oscillators in each channel. Provided the CCOs are well matched, the clock frequencies of all channels (RXCK0..n) are identical to HFCK.

Fig. 6: Multi-channel GCCO CDR

At each data edge, an edge detection circuit based on a delay line and an XOR gate generates a synchronization signal EDET for the GCCO (Figure 7). For better isolation, the whole design is realized using fully-differential currentmode logic gates.

Fig. 7: Gated oscillator with edge detection

At an incoming data edge (D IN ), EDET goes low for a duration defined by the delay of the edge detector delay line (Figure 8). The first stage of the oscillator is frozen to a high state, which propagates through the oscillator and reaches the clock output after half a clock period (T/2).

Frequency tolerance

Unlike in PLL-based or phase-interpolated clock recovery circuits, there may be a frequency difference between the gated oscillator in the receiver of a given channel and the incoming data stream. In practical applications, the data rate is specified to ±100ppm. The frequency tolerance (FTOL), defined as the maximum frequency difference at which the BER remains lower than 10 -12 specifies the requirements on frequency stability of the gated oscillator design.

8bit/10bit encoding schemes used in short-distance communications reduce the effective data rate by 20%, but limit the number of consecutive identical digits (CID) to five. This is the worst case for accumulation of jitter and frequency error, to be taken into account in the analysis of JTOL and FTOL.

Behavioral modeling

Statistical model

Considering the gated CCO topology shown in Figure 7, we implemented a Matlab model to analyze JTOL and FTOL and the resulting BER with respect to incoming jitter, oscillator jitter and CID. In statistical models, the exact contributions of different types of timing jitter can be accurately combined. Deterministic jitter is modeled with a uniform probability density function (PDF), random jitter with a normal PDF and sinusoidal jitter leads to a sine wave histogram distribution.

The following simulations were all performed with the jitter specifications given in Table 1. 9 shows the achievable bit error rate when applying additional sinusoidal jitter. The targeted bit error rate of 10 -12 is much above the specifications of Figure 5, especially for low-frequency jitter.

Fig. 9: BER as a function of sinusoidal jitter frequency (normalized to data rate) and amplitude

When frequency offset is present, the accumulated frequency difference over several CID is harmful to the performance of the gated-oscillator CDR (Figure 10).

Fig. 10: BER with frequency offset of 1%

For jitter frequencies close to the data rate, the estimated jitter tolerance for a BER of 10 -12 drops below the tolerance mask. This shows that there is very little design margin in oscillation frequency and oscillator phase noise.

Phase noise estimation

Frequency stability, already discussed, and timing jitter are the two most important specifications of the oscillator in the GCCO topology. Timing jitter of ring oscillators, or its frequency domain analogy phase noise, have been extensively studied [START_REF] Weigandt | Analysis of timing jitter in CMOS ring oscillators[END_REF]- [7].

Fig. 11: Phase noise-power consumption trade-off

The oscillator bias currents and derived device dimensions are chosen based on this graph. The respective standard deviation for the sampling clock is 0.01UI RMS for CID = 5.

VHDL model

All system components have been modeled in VHDL to perform behavioral verification in the time domain. The statistical model previously discussed gives a good estimate of achievable performance, but it would be difficult to introduce temporal behavior and non-ideal gate delays in the statistical models. The behavioral model is close to the physical implementation, as shown in Figure 12, and considers most contributions to jitter and static phase error.

Unlike the transistor-level simulation, the CPU requirements are sufficiently low to run parametric simulations on frequency offset and jitter contributions (10µs simulated in ~ 45min). The gate-level VHDL model, taking into account jitter components and delay non-maximum κ

Bit Error Ratio

Bit Error Ratio

idealities, can thus be used for extensive verification of the CDR topology.

VHDL and Matlab simulations are based on the same specifications in terms of jitter and frequency tolerance. Deterministic, random and sinusoidal jitter are applied to the incoming data stream. The phase noise of each cell of the delay line and the GCCO is independently calculated as a random delay variation. Amplitude noise is neglected. This assumption is commonly accepted for clock recovery circuits, as the pre-amplification in the system delivers binary signals. (cdr_gvco_enable and cdr_gcco_nreset)) after delay0; vinv2 <= transport not(vinv1) after delay1; vinv3 <= transport not(vinv2) after delay2; vinv4 <= transport not(vinv3) after delay3; cdr_gcco_ckout <= not(vinv4); end bhv;

Fig. 12: VHDL code of gated CCO

The contribution of the VHDL model to design verification will be illustrated by two concrete issues raised and solved with this approach.

a. Delay in the edge detector

The behavioral models include gate delays and timing jitter in the ring oscillator components. The current-mode logic cells used in this design exhibit different input to output delays for the different inputs, due to the stacked nature of the design. These different delays must be taken into account in this kind of simulation.

Although the chosen topology should be insensitive to the exact delay of the delay line in the edge detector, VHDL simulations raised concerns about this hypothesis. Figure 13 shows that if the rising edge of EDET occurs before the forth stage of the oscillator (CK OUT ) has gone low, the oscillator will not be synchronized with the respective data edge.

If the oscillator frequency is close to the data rate, this can happen for tens or more consecutive data edges, leading to poor jitter tolerance. Detailed analysis showed that reliable operation is guaranteed for T/2 < τ < T. EDET As the whole CDR is designed using fully differential logic gates for proper high speed operation, the change of sign of the clock signal compared to the topology in Figure 7 is taken care of by inverting the differential output signal. This does not require any additional logic gates, which would introduce critical delay in the clock path.

Fig. 15: Modified GCCO topology

The simulation results in Figure 16 show an obvious improvement in timing margin on the right data edge, i.e. the eye opening is almost symmetrical around UI/2. Note that in both cases, a standard pseudo-random bit sequence (PRBS7) was applied, which exhibits more consecutive identical digits than an 8bit/10bit encoded stream. 17). While the topology directly improves the horizontal eye opening as shown above, this sampling point may however increase the probability of erroneous sampling of the next bit due to frequency offset, not considered in Figure 17.

Transistor-level design

Based on the high-level simulations and phase noise estimations previously discussed, we designed the gated CCO clock and data recovery circuit in a 0.18µm CMOS digital process from UMC.

Fig. 18: Eye diagram from transistor-level simulation (typical case, no jitter applied)

While detailed discussion of the transistor-level design is beyond the scope of this paper, Figure 18 shows the output eye diagram obtained in typical case simulation. The layout of the test chip is to be completed by the time of publication. Experimental results will be presented in a follow-up paper.

Conclusion

We presented a design flow to achieve a low-power multi-channel clock and data recovery circuit. The flow allowed us to have a good estimate of the achievable bit error rate of this topology through statistical simulations. Using behavioral VHDL modeling, we were able to improve the bit error rate of this solution by introducing minor changes in the topology. These changes were extensively verified in various jitter and frequency offset configurations. The design flow presented here serves as a convincing demonstration that a complete top-down approach can be implemented in the design of demanding high-speed analog ICs.

This research has been supported in part by the Swiss National Science Foundation Grant 200021-100625.

Fig. 8 :

 8 Fig. 8: Timing diagram of GCCOAt the rising edge of EDET, the oscillator is released and goes back to free oscillation at the frequency determined by its control current. As the data fed to the sampler (DD IN ) is taken at the output of the edge detector, the delay and jitter introduced by the delay line do not influence on the precision of the sampling. Parasitic delays coming from the XOR gate or the delay mismatch between both inputs of the NAND gate in the oscillator are compensated for by dummy gates. All delay cells in the delay line and the ring oscillator are built with identical current-mode logic two-input gates.

  Hajimiri) allows us to derive the phase noise -power consumption trade-off of the ring oscillator, shown in Figure 11, in comparison with a variation of McNeill's formula. I SS is the bias current of one oscillator stage, R L its load resistance, ∆V the signal swing, γ the noise factor of the active devices and η indicates the relationship between rise-time and cell delay.

  gain [Hz/A] cdr_gcco_fc: real; --Free-running frequency [Hz] cdr_gcco_cc0: voltage; --Control current mid-point [C] cdr_gcco_jit_sigma: real); --defined as a ratio, e.g 1%->0.01 port ( […]); end entity cdr_gcco; architecture bhv of cdr_gcco is […] begin --ring_osc calc_delay0: process begin --process calc_delay awgn(seed1, seed2, mean, sigma, jitter); --gaussian random gen. [8] delay0 <= 1 ps * 1.0e12/ (8.0*(cdr_gcco_fc+cdr_gcco_k*(cctrl-cdr_gcco_cc0))) * (1.0+jitter); wait for delay0; end process calc_delay0; […] --calculation of the three remaining delays vinv1(0) <= transport (vinv4(0) and cdr_gcco_trig(0)) and (cdr_gvco_enable and cdr_gcco_nreset) after delay0; vinv1(1) <= transport ((vinv4(0) nand cdr_gcco_trig(0)) and

3 Fig. 13 :

 313 Fig. 13: Problem situation for τ T/2 b. Optimum sampling pointAn even more interesting consideration in the behavioral simulations is the selection of the optimum sampling instant. As the oscillator is triggered by each incoming data edge, the left data edge in the eye diagram has a narrow distribution, while the right edge suffers of accumulated jitter and frequency error over several CID (Figure14).In order to plot the output data eye diagram as it occurs at the sampler input, an eye generator block in VHDL has been inserted. Unlike eye diagram features in conventional tools, it does not use fixed time sampling intervals, but aligns the data on the rising edge of the sampling clock. The aligned data is send to a text file, which can be easily read into Matlab to plot the eye diagram shown below.

Fig. 14 :

 14 Fig. 14: 25k cycles PRBS7 eye diagram simulated in VHDL with: CCO frequency = 2.375GHz sin. jitter amp = 0.10UI pp , freq = 250 MHzIn order to increase the BER, the sampling instant has been shifted by one eighth of the clock period, using the inverted output of the third inverter stage as recovered clock (Figure15).As the whole CDR is designed using fully differential logic gates for proper high speed operation, the change of sign of the clock signal compared to the topology in Figure7is taken care of by inverting the differential output signal. This does not require any additional logic gates, which would introduce critical delay in the clock path.

Fig. 16 :Fig. 17 :

 1617 Fig. 16: Eye diagram with improved oscillator output (same conditions)

Table 1 : Jitter specifications for simulations

 1

	Jitter Type	Units	Value
	Deterministic (DJ)	UI PP	0.4
	Random (RJ)	UI RMS	0.021 (0.3 UI PP )
	Sinusoidal (SJ)	UI PP	swept
	Oscillator (CKJ)	UI RMS	0.01
	Figure

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400ps

Bit Error Ratio