TO DO - Need to Summarize the following research paper and comment on the direction they could go next or how to make the paper better! (your own Idea) WORD LIMIT - 250 ( altogether), MLA/n frontiers in Pharmacology REVIEW published: 03 February 2021 doi: 10.3389/fphar.2021.601626 Check for updates Biodegradable Polymeric Nanoparticles for Drug Delivery to Solid Tumors Agnese Gagliardi¹t, Elena Giuliano ¹t, Eeda Venkateswararao², Massimo Fresta¹, Stefania Bulotta 1*, Vibhudutta Awasthi²* and Donato Cosco 1* 1 Department of Health Sciences, University "Magna Græcia" of Catanzaro, Catanzaro, Italy, 2 Department of Pharmaceutical Sciences, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States OPEN ACCESS Edited by: Santiago Gómez-Ruiz, Rey Juan Carlos University, Spain Reviewed by: Kui Luo, Sichuan University, China Xiaowei Zeng, Sun Yat-Sen University, China *Correspondence: Stefania Bulotta bulotta@unicz.it Vibhudutta Awasthi vawasthi@ouhsc.edu Donato Cosco donatocosco@unicz.it These authors have contributed equally to this work Specialty section: This article was submitted to Experimental Pharmacology and Drug Discovery, a section of the journal Frontiers in Pharmacology Received: 01 September 2020 Accepted: 04 January 2021 Published: 03 February 2021 Citation: Gagliardi A, Giuliano E, Venkateswararao E, Fresta M, Bulotta S, Awasthi V and Cosco D (2021) Biodegradable Polymeric Nanoparticles for Drug Delivery to Solid Tumors. Front. Pharmacol. 12:601626. doi: 10.3389/fphar.2021.601626 Advances in nanotechnology have favored the development of novel colloidal formulations able to modulate the pharmacological and biopharmaceutical properties of drugs. The peculiar physico-chemical and technological properties of nanomaterial-based therapeutics have allowed for several successful applications in the treatment of cancer. The size, shape, charge and patterning of nanoscale therapeutic molecules are parameters that need to be investigated and modulated in order to promote and optimize cell and tissue interaction. In this review, the use of polymeric nanoparticles as drug delivery systems of anticancer compounds, their physico-chemical properties and their ability to be efficiently localized in specific tumor tissues have been described. The nanoencapsulation of antitumor active compounds in polymeric systems is a promising approach to improve the efficacy of various tumor treatments. Keywords: surfactants, PEG, polymeric nanoparticles, passive targeting, cancer INTRODUCTION Cancer is the second leading cause of death in the world, and was responsible for approximately 9.6 million deaths in 2018 (Bray et al., 2018). Over the next 20 years, the number of new cases is estimated to increase by about 70% (Siegel et al., 2017). Cancer therapy is considered a multidisciplinary challenge requiring close collaboration among clinicians, biologists, and biomedical engineers (Danhier et al., 2010). Current cancer treatments include surgery, radiation, and chemotherapy, but the effects of these procedures may cause damage to normal as well as tumoral cells. The resultant systemic toxicity and adverse effects greatly limit the maximum tolerated dose of anti-cancer drugs, and thus restrict their therapeutic efficacy. In particular, surgery together with radiotherapy are the first choice used for local and non-metastatic cancers, while anti- cancer drugs (chemotherapy, hormone, and biological therapies) are the treatments currently employed in metastatic cancers and adjuvant therapies (Tran et al., 2017). The toxicity of conventional chemotherapeutic drugs, as well as the indiscriminate destruction of healthy cells and the development of multidrug resistance, are the motivating thrust behind research on novel targeted treatments (Pérez-Herrero and Fernández-Medarde, 2015; Tran et al., 2017). The main challenge is to improve the selectivity of anticancer drugs for tumor cells and the tumor microenvironment, while sparing healthy cells and tissues. In this context, a promising approach is the targeting of tumor tissue by nanomedicine-based therapeutics (Oerlemans et al., 2010). These formulations are made up of submicrometer-sized carriers containing the active compound(s), which are able to selectively diagnose and treat tumors by suitable targeting vectors, thus improving the therapeutic index and the pharmacokinetic profile of the anticancer drugs that are delivered. Frontiers in Pharmacology | www.frontiersin.org 1 February 2021 | Volume 12 | Article 601626 Gagliardi et al. Polymeric Nanoparticles as Antitumor Nanomedicine Polymeric Nanoparticles Solid Tumor Drug Targeting Natural Synthetic Size Biopolymers Surface Polydispersity Preparation Nanosphere Polymeric Shell Chemisti Properties Oncological Applications Polymeric Matrix Drug Clinical and preclinical investigation Immunotherapy FIGURE 1 | Overview of the main features of polymeric nanoparticles. Nanocapsule Polymeric Nanoparticles Future perspectives Nanocarriers can retain multiple therapeutic agents not only to enhance their therapeutic effect on a synergestic or additive basis, but also to overcome acquired resistance to single chemotherapeutic drugs. Many tumors develop chemo- resistance through many mechanisms, including induction of the drug efflux rate or the downregulation of uptake mechanisms (Mansoori et al., 2017). Nanoparticulate formulations can overcome this limitation by providing an alternative pathway of cellular internalization. Currently, several therapeutic nanoparticle platforms are being investigated for targeted cancer treatment, including lipid-based, polymer-based, inorganic, viral, and polymer-drug conjugated systems. In the past two decades, over 20 nanotechnology-based therapeutic products have been approved for clinical use. Among these products, liposomal systems and polymer-drug conjugates are two of the most important groups, and many other formulations are under clinical investigation, including chemotherapy, hyperthermia, radiation therapy, gene or RNA interference (RNAi) therapy, and immunotherapy (Wicki et al., 2015). Nanocarriers have unique features such as their nanometric size, high surface area-to-volume ratio, favorable drug release profiles and targeting features which can promote their preferential accumulation in tumor tissues (Wicki et al., 2015). Most nanosystems for the treatment of solid tumors are administered systemically and accumulated in the tumor tissues through the enhanced permeability and retention (EPR) effect, which is generally thought to be the result of leaky tumor vasculature and poor lymphatic drainage (Maeda, 2015). However, this interpretation of EPR-dependence is simplistic, because the biodistribution of systemically administerd nanosystems can be influenced by multiple biological factors, including interaction with plasma proteins, blood circulation time, extravasation, penetration of tumor tissue, and cancer cell uptake (Shi et al., 2017). Modification of the surfaces of the nano-systems-which are able to confer specific targeting properties or stimuli-sensitive responses—also affect their overall distribution. Much of our current knowledge regarding the in vivo behavior of nanoparticulate systems is based on data obtained from animal models. But relatively few investigations have correlated the obtained data in order to determine whether and how the safety and the efficacy of nanoparticles in humans can be better predicted by using these animal models (Hrkach et al., 2012; Zuckerman et al., 2014). There also exist a number of scientific articles which focus on specific aspects and applications concerning the development of polymeric nanoparticles. Frontiers in Pharmacology | www.frontiersin.org 2 February 2021 | Volume 12 | Article 601626 Gagliardi et al. Macrophage # Cancer Cells Red Cells Polymeric Nanoparticles as Antitumor Nanomedicine Endothelial Cells Fibroblast # Collagen Fibers Physiological Environment Pericyte FIGURE 2 | Differences between a physiological and a tumor environment. Figure generated from Servier Medical Art. Tumor Environment Therefore, this work is not intended to be a review of all the research performed in this area, but rather to provide the basic concepts and ideas related to the preparation and use of polymer- based nanoparticles as drug carriers in cancer therapy. This article offers an overview and discusses the most important findings and prospects as illustrated in Figure 1. TUMOR MICROENVIRONMENT The microenvironment of tumor tissue significantly differs from that of healthy tissue. These differences include vascular abnormalities, oxygenation and perfusion levels, pH, and metabolic status (Abadjian et al., 2017). Solid tumors are characterized by a heterogeneous population of neoplastic cells supplied by an irregular and discontinuous endothelium with large gaps between the endothelial cells, and abnormally thick or thin basement membranes where pericites are loosely attached to endothelial cells (Figure 2). The irregularity of tumor blood vessels in their distribution, diameter, density, and serpentine shape, can be the cause of poor perfusion which leads to excessive fluid extravasation (Khawar et al., 2015). The two main causes of this heterogeneity are spatial stress, resulting from rapid tumor growth, and the abnormal extracellular matrix which can compress the vessels and partially block the flow of blood [which causes the escape of plasma and a high interstitial fluid pressure (IFP)] (Jain, 2013). The IFP is highest at the center of solid tumors and decreases radially, creating a movement of fluid away from the central region of the tumor. This phenomenon contributes to a reduced transcapillary transport of therapeutic drugs as well as their scarce accumulation in the middle of the tumor (Danhier et al., 2010). The elevated IFP and associated peritumoral edema also assist in the transport of growth factors and cancer cells away from the tumor, thus favoring tumor progression, while the abnormal and disorganized tumor vasculature results in inefficient blood flow inside the tumor mass, hypoxia, and low extracellular pH (Khawar et al., 2015). Hypoxia plays a crucial role in tumor growth and metastasis through the induction of molecular signaling which is responsible for genetic instability, inflammation, immunosuppression, epithelial-mesenchymal transition and altered metabolism (Jing et al., 2019). It also confers resistance against several kinds of treatment, such as radiation, chemo-, photodynamic and immunotherapies, which require oxygen for efficacy (Jain, 2013). By virtue of the hypoxia-inducible factor-mediated pathway, hypoxia promotes angiogenesis. Oxygen can diffuse for maximum 150 μm beyond the capillary wall, which implies that when a tumor reaches a certain size (~2 mm³), a state of cellular hypoxia begins. Angiogenesis is a cellular mechanism which is upregulated in tumoral microenvironments and creates new blood vessels to further assist tumor growth by supplying oxygen and nutrients (Jászai and Schmidt, 2019). This process consists of five steps: i) endothelial cell activation, ii) basement membrane degradation, iii) endothelial cell migration, iv) new vessel formation, and v) angiogenic remodeling. In the first phase, hypoxia induces an increase of the hypoxia-inducible factor- mediated transcription of pro-angiogenic proteins such as vascular endothelial growth factor (VEGF), platelet-derived growth factor (PDGF), and tumor necrosis factor-a (TNF-α) (Wigerup et al., 2016). Activated endothelium regulates the migration of endothelial cells through the extracellular matrix during vessel formation, due to the expression of a dimeric Frontiers in Pharmacology | www.frontiersin.org 3 February 2021 | Volume 12 | Article 601626 Gagliardi et al. Polymeric Nanoparticles as Antitumor Nanomedicine transmembrane integrin avß3 which interacts with the proteins of the extracellular matrix (vitronectin, fibronectin, etc.) (Demircioglu and Hodivala-Dilke, 2016). Successively, the matrix metalloproteinases synthesized by the activated endothelial cells degrade the basement membrane and the extracellular matrix. This process causes the apoptosis of the inner layer of endothelial cells, leading to the formation of a vessel lumen and remodeling of the immature vasculature, stabilized by pericytes and smooth-muscle cells. Often this step remains incomplete, resulting in irregularly-shaped, dilated, and tortuous tumor blood vessels. The angiogenic switch is the crucial phase in which a tumor changes from a non- angiogenic to an angiogenic phenotype and allows the dissemination of cancer cells throughout the body (Jászai and Schmidt, 2019). Hypoxia also results in metabolic acidosis caused by increased glycolysis (the Warburg effect); this lowers the extracellular pH to 6.0-7.0 (De Palma et al., 2017). Acidosis is also a factor in epithelial-mesenchymal transition and it synergistically contributes to tumor invasion and metastasis (Yang et al., 2016). Because of their rapid growth, tumor cells continue to exploit glycolysis as an ATP-generating pathway even when oxygen is available, lowering dependence on glucose oxidation for energy production (Fu et al., 2017). This metabolic preference is mostly due to defective mitochondrial function (Kim et al., 2009). The elevated breakdown of glucose produces large amounts of lactic acid and significant amounts of free protons (H+) which are pumped into the extracellular milieu by mechanisms involving the carbonic anhydrases IX and XII (Martinez-Outschoorn et al., 2017). The resulting pH gradients between intra- and extracellular compartments within the tumor tissue, as well as between the tumor mass and the general host tissue, are potential sources of variable and often inefficient partitioning and distribution of drugs. Exposure to chemotherapy may favor the selection of tumor-cell clones with acidic organelles, which are able to entrap the drugs, and if these organelles are part of the secretory pathway, then the drug will be transported out of the cell through exocytosis. All these factors in the tumor microenvironment contribute to multidrug resistance (MDR) phenomena (Danhier et al., 2010). POLYMERIC NANOPARTICLES Over the last decade nanoparticles have become extremely attractive for application in biology and medicine (Mogoşanu et al., 2016). They have the potential to modulate biopharmaceutical features, pharmacokinetic properties, and the therapeutic efficacy of entrapped drugs (Dang and Guan, 2020). Technically, nanoparticles are defined as being less than 100 nm, but in practice structures up to 300 nm in size are included in this category (Guo et al., 2016), and they can fall into different classes as a function of their morphology, size, composition, and physicochemical properties (Khan et al., 2019). Polymer-based nanoparticles are colloidal systems made up of natural or synthetic polymers. They furnish significant advantages over other nanocarriers such as liposomes, micelles and inorganic nanosystems, and include the feasibility of scale-up and the manufacturing process under Good Manufacturing Practices (GMP) (van Vlerken et al., 2007). Other peculiar characteristics of polymeric nanoparticles are the significant stability of polymeric nanoparticles in biological fluids along with the wide availability of various polymers, the opportunity to functionalize their surfaces and to modulate polymer degradation and the leakge of the entrapped compound(s) as a function of specific stimuli (Venkatraman et al., 2010; Goodall et al., 2015; Sarcan et al., 2018). Several chemotherapeutics have been encapsulated in polymeric delivery systems, with the aim of increasing antitumor efficacy, inhibiting metastases, and decreasing the effective dose and side effects. Polymers can encapsulate an active compound within their structure or adsorb it onto their surfaces (Masood, 2016). Langer and Folkman were the first to demonstrate the controlled release of macromolecules using polymers, which allowed the development of antiangiogenic drug delivery systems for cancer therapy (Langer and Folkman, 1976). Ideally, the polymers selected for parenteral administration must be biocompatible, biodegradable, and possess specific mechanical and physicochemical properties (Vilar et al., 2012). The first polymers used to develop polymeric nanoparticles (PNs) were non-biodegradable polymers, such as poly(methyl methacrylate) (PMMA), polyacrylamide, polystyrene, and polyacrylates. The nanosystems made up of these materials exhibited a rapid and efficient clearance, but chronic toxicity and inflammatory reactions were observed. Usually, non-degradable polymers require degradation times longer than their effective duration of application (Anju et al., 2020), whereas the degradation rate of biodegradable polymeric nanoparticles can be influenced by several parameters, including their physico-chemical properties (size, structure, molecular weight) and external factors, such as pH and temperature (Su and Kang, 2020). Although pioneering studies on polymeric nanoparticles have focused on non-degradable materials, the use of biodegradable polymers had a great impact as a consequence of their notable biocompatibility and biosafety (Kamaly et al., 2016). Biodegradable polymers include synthetic polymers such as poly(D,L-lactide) (PLA), poly(D,L-glycolide) (PLG), co-polymer poly(lactide-co-glycolide) (PLGA), polyalkylcyanoacrylates, poly-Ɛ-caprolactone. They are considered safe and a few biodegradable polymer products have been approved by the US Food and Drug Administration (FDA) as well as by the European Medicines Agency (EMA) for pharmaceutical application (Palma et al., 2018). In general, biodegradable polymeric particles show reduced systemic toxicity, are more biocompatible, and favor modulation of drug-release kinetics. They are typically degraded into oligomers and monomers, which are further metabolized and eliminated from the body via normal pathways (Ravivarapu et al., 2006; Vilar et al., 2012). Non- synthetic biodegradable polymers, which include natural polymers such as chitosan, alginate, gelatin, zein, and albumin, have also been used to prepare polymeric nanoparticles (Gagliardi et al., 2018). We will discuss commonly-used Frontiers in Pharmacology | www.frontiersin.org 4 February 2021 | Volume 12 | Article 601626 Gagliardi et al. Polymeric Nanoparticles as Antitumor Nanomedicine polymers for the preparation of drug-loaded PNs for anticancer therapy later. Biopolymers for Cancer Nanomedicine Biopolymers are one of the most important classes of biomaterials (Anju et al., 2020) and are widely used in biomedical applications because of their biocompatibility and biodegradability (Jaimes- Aguirre et al., 2016). They are macromolecules made up of repeating monomeric subunits linked by covalent bonds (Wen et al., 2018). Based on their origin, biopolymers are divided into natural and synthetic classes (Taghipour-Sabzevar et al., 2019). The advantages and disadvantages of these biopolymers are taken into consideration during selection for the development of a drug delivery system. Synthetic Biopolymers Synthetic biopolymers can be derived from natural polymers or chemically synthesized. They have attracted much attention because of their stability, flexibility, low immunogenicity, and biodegradability. Since they resist hydrolysis and can tolerate high temperatures, they can be heat-sterilized without degradation (Rahman and Hasan, 2019). Poly (a-hydroxy acids), polyhydroxyalkanoates (PHAs), poly (lactones), and poly(alkyl cyanoacrylates) (PACA) are the common synthetic biopolymers, among which poly (a-hydroxy acids) are the most employed class of biopolymers for production of PNs. Poly (a-hydroxy acids) are degraded by non-enzymatic hydrolysis of the ester linkage into non-toxic monomers (lactic acid and glycolic acid). Their degradation rate depends on intrinsic properties such as molecular weight, chemical structure and hydrophobicity (Doppalapudi et al., 2016). Nanoparticles made up of these polymers have been developed for the delivery of various hydrophilic and hydrophobic anti- cancer agents such as doxorubicin, 5-fluorouracil, cisplatin, paclitaxel, and docetaxel (Rafiei and Haddadi, 2017; Ashour et al., 2019; Domínguez-Ríos et al., 2019; Maksimenko et al., 2019; Mittal et al., 2019). PLG was the first polymer of this class investigated for biomedical application (Doppalapudi et al., 2016). It is synthesized through the polycondensation of glycolic acid or ring opening of glycolide, but it is not a good choice for the formulation of nanocarriers for cancer therapeutics because of its rigidity and rapid degradation (Shukla et al., 2019). PLA, another widely-investigated polymer, can be obtained from the polycondensation of lactic acid (LA) or by the ring opening polymerization of lactide; it exists in two isomeric forms, poly(L-lactic acid) and poly(D-lactic acid) (Fonseca et al., 2015). PLA naturally degrades in situ through the hydrolysis of the ester linkage, rendering LA and its short oligomers as the degradation products. Since the products of PLA biodegradation are cleared easily from the body, its use does not induce severe immune responses (Lee et al., 2016; Casalini et al., 2019). Among polyesters, PLGA is the most widely-used co-polymer for the development of targeted drug delivery systems, and is made up of glycolic acid and lactic acid monomers (Mir et al., 2017; Maity and Chakraborti, 2020). PLGA polymers undergo complete biodegradation in aqueous media and their characteristics can be altered by varying the chemical composition (lactide/glycolide ratio) and the chain length. For example, the degradation rate and the drug-release rate accelerate when the molecular weight of the copolymer is decreased (Molavi et al., 2020). PLGA can be prepared at different lactide/glycolide molar ratios such as 50/50, 65/35, 75/25, and 85/15. Lactide is more hydrophobic than glycolide, so a decrease in the proportion of lactide increases the rate of hydrolytic degradation of the copolymer, with consequent rapid release of the encapsulated drug (Gentile et al., 2014). It has been suggested that the degradation times of 50/50, 75/25 and 85/15 PLGA is 1-2, 4-5, and 5-6 months, respectively (Middleton and Tipton, 1998; Anju et al., 2020). Biopolymers produced by microorganisms have shown promise as a substitute for the synthetic polymers currently being used in the industry. For instance, PHAs are naturally produced and accumulated as energy/carbon storage material by many bacteria. PHAs have recently gained great attention because of their biocompatibility, biodegradability, thermoplasticity, low toxicity, and availability (Korde and Kandasubramanian, 2020). They are polyesters of various hydroxyalkanoate monomers that can be produced either through the natural bioconversion process or by chemical synthesis via the ring-opening polymerization of ẞ-lactones (Li and Loh, 2017). Poly(hydroxybutyrate) (PHB) is a PHA derivative used in targeted drug delivery due to its prolonged degradation time in vivo and its lesser effect on the pH of tissues as compared to the polylactides (Korde and Kandasubramanian, 2020). According to ISO 10993, PHB nanoparticles have been shown to be safe when used on animals (Masood, 2016). Among polylactone-based polymers, poly(Ɛ-caprolactone) (PCL) is the most studied polymer for anticancer drug development. It is a semicrystalline compound obtained by the ring-opening polymerization of ε-caprolactone (Witt et al., 2019). PCL exhibits slower ester bond hydrolysis at physiological pH and has a less acidic character than poly-hydroxy acids; in addition, the slower degradation rate of PCL prolongs the release of encapsulated drugs (Doppalapudi et al., 2016). Poly(alkyl cyanoacrylates) (PACA) are another biodegradable polymer class useful for developing nanocarriers. These polymers are mainly degraded through the hydrolysis of the ester bonds of their alkyl chain. The rate of degradation depends on the alkyl chain length: the longer the alkyl chain, the slower the rate. The two resulting products, namely alkyl alcohol and poly (cyano acrylic acid), are both soluble in water (Nicolas and Couvreur, 2009; Doppalapudi et al., 2016). PACAs can retain substantial amounts of drug (Sulheim et al., 2017). Poly(isohexylcyanoacrylate) nanoparticles containing doxorubicin (Livatag®-see section “Livatag®”.) have been proposed as an innovative formulation for human primary liver cancer and have reached phase III of clinical trials (Merle et al., 2017). Natural Biopolymers Natural biopolymers include animal- or plant-derived proteins and polysaccharides as well as polymers obtained from microbial sources. These are widely used in drug delivery research due to Frontiers in Pharmacology | www.frontiersin.org 5 February 2021 | Volume 12 | Article 601626

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TO DO - Need to Summarize the following research paper and comment on the direction they could go next or how to make the paper better! (your own Idea) WORD LIMIT - 250 ( altogether), MLA/n frontiers in Pharmacology REVIEW published: 03 February 2021 doi: 10.3389/fphar.2021.601626 Check for updates Biodegradable Polym

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Make a graph of column F in the isometric weights spreadsheet (50 lb column). What part of the typical processing of EMG does the signal in the F column look like?

In an experiment the transport of the neurotransmitter serotonin into cultured mammalian cells was measured. Batches of cells were incubated with solutions of different concentrations of radio labelled [3H]-serotonin for a defined time, cells were then separated from the incubation buffer, and serotonin accumulated into the cells was determined by scintillation counting. The rate of transport is given as dpm/min* (see table below). In order to elucidate the transport mechanism, the experiment was conducted under two different conditions, i.e., in condition A normal transport buffer was used, and in condition B the transport buffer did not contain any Na* ions.[Notes: * dpm/min means disintegrations per minute and is a measure of the intensity of-radioactivity of a radio-labelled compound; it is directly related to the rate of transport for this compound] 11. Draw a graph (by using Excel or similar), plotting the serotonin concentration against the-transport rate under both conditions. (5 Marks). 12. What transport rates for each condition would you expect if the experiment was repeated-using 12μM [³H] serotonin? Add your estimate into the table above. (5 Marks). 13. Examine the plot obtained for condition A; what can you conclude with regards to-whether or not the transport of serotonin into these cells requires a protein? Explain your conclusion. (10 Marks). 14. Compare the plots of the transport rates for both conditions. What is most likely mechanism of transport for serotonin into these cells? Explain your interpretation. (10Marks).

1- Write an essay on the importance of anthropometry and how anthropometric data can be used in the design of workplaces to protect the workers from work-related musculoskeletal disorders.

1. Why is it necessary to maintain aseptic conditions in microbiology? 2. Explain why the following steps are necessary during sub culturing: dFlaming the inoculating loop before and after each inoculation (= b. Cooling the inoculating loop before touching the inoculum/culture ( Flaming the neck of tubes/bottles after capping and before re-capping ( Can pure culture be prepared directly from a mixed culture? Explain your answer. 4. You have been asked to determine the bacterial count in a sample of water. The-number of CFU from 1 ml of a 106 dilution was 43 and 49 on duplicate agar plates.per ml of the original sample of water? (5What is the total number of microorganisms-marks)

5. [Total: 8 pts] Muscle stretch reflex The figure below shows a simplified model of muscle stretch reflex in an experimental anesthetized animal. The model describes how the muscle stretch reflex regulates the muscle length. All variables shown have been linearized and represent fluctuations around its mean value under normal resting condition. Z represents external neural frequency stimulating the spinal cord. fa represents the total change in afferent neural frequency. The spinal cord, represented by the gain Gc, converts the incoming neural input to the neural output fe- The changes in the efferent neural frequency, fe, are relayed through motor neurons to the muscle. The muscle converts the efferent neural frequency to changes in muscle length L. The gain of this conversion is-G. Note that the gain is negative because increases in efferent neural frequency lead to decreases in muscle length. The change in the muscle length is sensed by the muscle spindle. The muscle spindle relays the neural output, fs, to the spinal cord through sensory neurons. This process is represented by the gain Gg. fa fe Gc Z -GM Gs fs L a) [4 pts] Suppose that animal A is injected with a drug that disrupts neurotransmission, blocking the sensory neurons. Under such condition, is the system operating as a negative feedback system? Explain your answer. Please also state which gain(s) is affected by the sensory nerve blockade. b) [4 pts] Under which condition between normal and sensory nerve blockade would result in stronger muscle contraction for the same level of the external stimulation Z? Explain your answer.

2. [15 pts] Assume the metabolic hyperbola for CO₂ given by the following equation: 863 - Vcoz V₁ PACO2 Pico2+ where the normal steady-state CO₂ production is 235 mL/min and the inspired CO₂ concentration (or volumetric fraction) is 0. Also, assume a dead-space ventilation rate of 1 L/min. Also, suppose the steady-state ventilatory response to CO₂ is given by the following equation: 32 Vc = Drive external +(1.46 + (Paco2-37) and Vc 20 Pa02-38.6) Note that the above equation is slightly modified from what we derived in class in that a constant term, Drive external is added to the equation. This drive represents an additional source of control that affects ventilatory response e.g., sleep-wake state, alertness, etc. At normal state (resting and awake), let Drive external = 0. a) [5 pts] Use MATLAB to plot the metabolic hyperbola for CO₂ and the ventilatory response to CO₂ under normal condition. Show both graphs on the same figure (see hold function). Label both axes with appropriate units. Also indicate which graph represents the me the metabolic hyperbola for CO₂ and which graph represents the ventilatory response to CO₂ (see legend function). The plot should show the range of ventilation from 0-20 L/min and the range of PACO₂ from 30-60 mmHg (see xlim and ylim functions). Determine the normal steady-state values of ventilation and Pacoz from the plot (e.g., click on the plot where you want to obtain the x-y coordinates). Note: For the metabolic hyperbola for CO₂, please plot V against PACO₂ i.e., you would take the dead-space ventilation into consideration. b) [4 pts] The onset of sleep causes the external drive to breathe to drop by -5 L/min. State which parameter changes and to what value. Show the graphs representing this situation and report the steady-state values of ventilation and Pacoz. c) [4 pts] Follows from b), how would inhalation of a gas mixture containing 3% CO₂ in air (i.e., volumetric fraction of 0.03) during sleep affect the steady-state values of ventilation and Pacoz? State which parameter changes and to what value. Show the graphs representing this situation and report the steady-state values of ventilation and Pacoz. You may assume that the subject is at sea level. d) [2pt] Copy and paste the MATLAB code you used in this question (all parts). You may take a picture of your MATLAB script, but please make sure that the code is clearly readable from the image.

1. [5 pts] Construct the glucose-insulin regulation model in Simulink as outlined in Fig. 3. The parameter values shown in Fig. 3 are the values of a normal adult. Set the Simulink model to run simulations for a total duration of 24 hours. Although Simulink generally assumes time to be measured in seconds, the units of the model parameters give time in hours-so, you can treat the durations you enter into Simulink as hours (instead of seconds). The initial conditions of normal blood glucose and insulin concentrations are 0.81 mg/mL and 0.055 mU/mL, respectively. These initial values of blood glucose and insulin concentrations should be set in the respective Integrator blocks (shown as in Simulink). To set the initial values in the integrator block, double click the block to open the Block Parameters window. Enter the initial value (e.g., 0.81 for glucose) in the Initial Condition field, and click OK. Run a simulation for a normal adult (Subject N) over 24 hours without any external glucose input (i.e., U(t) = 0). Show the graph of glucose and insulin concentrations as a function of time as 2-by-1 subplots i.e., the glucose concentration is the top subplot and the insulin concentration is the bottom subplot. Label all axes. You may plot using the Scope in Simulink or plot in MATLAB using the simulation results that are sent to MATLAB Workspace. Save this Simulink model as "glucose_N.slx".

- *S5: Discuss appropriate and informed career management choices and entrepreneurial issues* - Consider including a section on the practical applications of studying flaviviruses and pseudotyped viruses in terms of career opportunities and entrepreneurship.

ments ons Button rations A https://uab.instructure.com/groups/346802/discussion_topics/7329486 pasting it into the reply area of the discussion. De sure to come back and respond to your group members. ib S R Description: UAB Hospital has decided to purchase a unique and very expensive type of MRI scanning equipment (to detect tumors). Look up some information on the internet about what is MRI equipment and how would it be used by a health care provider. The General Electric Company (GE) is a major provider of MRI equipment. It is important for the sales manager of GE Healthcare to understand who is likely to be involved in the buying center for this purchase at UAB Hospital. Each person may influence the purchase and perhaps influence it in different ways. The sales manager needs to see if all of the different buyer center's needs are being met, and if not, why not. Clearly, this kind of thinking can help guide the sales strategy. See the section in the book about "Multiple buying influence in a buying center" for more discussion of the buying center concept. INITIAL POST: In a few sentences, introduce yourself to your new discussion group. . Then address these points related to the case above: . Who might be involved in the buying center? • Explain your answer and describe the type of influence that different people in the buying center at UAB Hospital would have on the purchase.

(A) Reverse engineer a piece of medical technology. This must include: 1. A brief history of the science leading to its development, and the development of the technology. 2. A careful, physical analysis of how the device works. This must include a schematic or diagram and the math describing the physics. 3. Evaluation of how the device is applied, the impact it has on humanity, and how it could be improved in the future. Citations of strong sources are required DEVICE: Defibrillator for each question