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Determine the semimajor axis and the eccentricity of the spacecraft's orbit whose position and velocity at a particular time is given as

Write a 1500-word response (excluding references) to the question below. Use APA citation. The anterior cingulate cortex (ACC) is found near the front of the brain and wraps around the head of the corpus callosum. Seizures arising from the cingulate gyrus can be difficult to diagnose and treat due to their deep and medial location. To improve the outcome of the epilepsy surgery in cingulate epilepsy surgery, it is important that we understand cingulate cortex and its epilepsy. Describe common clinical seizure semiologies of the cingulate? Explain how this seizure type is classified? Discuss the role of non-invasive investigations in non-lesional cases. Include a discussion on the localisation of ictal EEG Explain why SEEG technique is favourable to explore the cingulate cortex compared to other invasive techniques. Compare and contrast subdural grid and SEEG technique? Describe challenges and pitfalls of diagnosis and treatment of medically refractory cingulate seizures.

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.

INSTRUCTIONS: Need help writing the abstract part of the given experiment. The experiment is "Microbial Production in a Bioreactor" Experimental details along with calculations details are attache (use them) Data in excel is given as well (use if required)

250 words Summarize the following research paper and comment on the direction they could go next! (your own Idea)--> It means What direction should the research go/n nature COMMUNICATIONS ARTICLE https://doi.org/10.1038/s41467-021-21047-0 OPEN Check for updates Activatable polymer nanoagonist for second near- infrared photothermal immunotherapy of cancer Yuyan Jiang, Jiaguo Huang, Cheng Xu¹ & Kanyi Pu? 1,2? Nanomedicine in combination with immunotherapy offers opportunities to treat cancer in a safe and effective manner; however, remote control of immune response with spatiotemporal precision remains challenging. We herein report a photothermally activatable polymeric pro- nanoagonist (APNA) that is specifically regulated by deep-tissue-penetrating second near- infrared (NIR-II) light for combinational photothermal immunotherapy. APNA is constructed from covalent conjugation of an immunostimulant onto a NIR-II semiconducting transducer through a labile thermo-responsive linker. Upon NIR-II photoirradiation, APNA mediates photothermal effect, which not only triggers tumor ablation and immunogenic cell death but also initiates the cleavage of thermolabile linker to liberate caged agonist for in-situ immune activation in deep solid tumor (8 mm). Such controlled immune regulation potentiates sys- temic antitumor immunity, leading to promoted cytotoxic T lymphocytes and helper T cell infiltration in distal tumor, lung and liver to inhibit cancer metastasis. Thereby, the present work illustrates a generic strategy to prepare pro-immunostimulants for spatiotemporal regulation of cancer nano-immunotherapy. 1 School of Chemical and Biomedical Engineering, Nanyang Technological University, Singapore, Singapore. 2 Division of Chemistry and Biological Chemistry, School of Physical and Mathematical Sciences, Nanyang Technological University, Singapore, Singapore. email: kypu@ntu.edu.sg NATURE COMMUNICATIONS | (2021)12:742 | https://doi.org/10.1038/s41467-021-21047-0 | www.nature.com/naturecommunications 1 ARTICLE NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-21047-0 mmunotherapy that boosts host immune system to fight against tumor has revolutionized cancer treatment 1,2. How- ever, single model immunotherapy often suffers from limited response rate and occasional immune-related adverse effects (irAEs) such as cytokine storm, hematopoietic system dysfunc- tion, and organ failure³. Nanomedicine thus has been brought into cancer immunotherapy in the hope to address these critical concerns in view of its tunable physicochemical properties to reinforce drug-immune cell interactions, and optimal pharma- cological profiles (e.g., biodistribution and retention) of immu- notherapeutic molecules 4-6. More importantly, nanomedicine serves as an assembly platform to allow additional therapeutic modalities (e.g., chemotherapy, phototherapy, radiotherapy, etc.) to be seamlessly integrated with immunotherapy to enhance therapeutic efficacy7-11. With the promise to improve immune response at no expense of breaking the systemic immune toler- ance, cancer nano-immunotherapy has been recently under extensive development. Further enhancement in the specificity of cancer immu- notherapy to facilitate its clinical translation mainly lies in the development of smart immunotherapeutic nanoagents with controlled activation 12-14. Till now, immunotherapeutic nanoa- gents have been programmed to unleash therapeutic action in response to biochemical indexes or cancer biomarkers such as pH, reactive oxidative species, and enzymes 15-18. For instance, human interleukin-15 super-agonist complex was engineered with disulfide-containing cross-linker for activatable release in response to T-cell receptor activation so as to improve therapeutic window of adjuvant cytokine therapy19. As another example, programmed cell death protein 1 antibody was specifically con- jugated to magnetic nanoclusters via pH-responsive benzoic- imine bond, leading to selective activation in the acidic intratu- moral microenvironment for potentiation of adoptive T-cell therapy 20. However, owing to their reliance on the difference of biomarkers at basal and pathological levels, the bioavailability and regional selectivity of immune activation for such immunother- apeutic nanoagents remain to be improved. In contrast to endogenous biomarkers, external stimuli are independent of the physiological environment and thus hold potential for more precise spatiotemporal and dosage control over immune regulation 12,21. Near-infrared light (NIR-I, 650-950 nm) is a popular external stimulus for the construction of smart nanomedicine owing to its minimal invasiveness and easy operation²². In particular, NIR-I light-responsive nanoagents have been developed to serve as the signal transducers to convert incident photons into regulatory signals, such as singlet oxygen to trigger the activation of indoleamine 2,3-dioxygenase 1 inhibitor, or high-energy emission to liberate CpG21,23. Superior to NIR-I light, second NIR light (NIR-II, 1000-1300 nm) has been recently revealed to possess even better biological transparency and fur- ther ameliorated phototoxicity with a lower maximum permis- sible exposure limit 24. However, few NIR-II nanotransducers are available, which include gold nanostructures25, transition metal- based nanoparticles26, and naphthalocyanine derivatives27. Recently, semiconducting polymer nanoparticles (SPNs) com- posed of highly ?-conjugated backbones have formed a promising class of NIR-II nanoagents 28,29. With their excellent photo- thermal performance and intrinsically benign compositions, SPNs have been exploited for deep-tissue molecular photoacoustic imaging³ photothermal therapy (PTT)³², and photothermal ferrotherapy33. However, the integration of SPNs with NIR-II light for spatiotemporal photoregulation of immunotherapy has yet to be explored. 30,31 We herein report the synthesis of an activatable polymer nanoagonist (APNA) for NIR-II light-regulated photothermal immunotherapy of cancer (Fig. 1). APNA is composed of a NIR- 2 II light-absorbing semiconducting polymer backbone as photo- thermal transducer, conjugated with a potent toll-like receptor type 7 and 8 (TLR7/8) agonist (Resiquimod: R848) as the immunostimulant through a thermolabile cleavable linker (2,2'- azobis [2-(2-imidazolin-2-yl)propane]: VA-044) (Fig. 1a). Mainly acting on antigen-presenting cells (APCs) such as dendritic cells (DCs), R848 helps upregulate secretion of crucial proin- flammatory cytokines and enhance maturation or polarization of APCs, priming T lymphocytes³4. Upon focal NIR-II photo- irradiation, APNA mediates photothermal effect to directly ablate tumor, and elicit immunogenic cell deaths (ICDs) of cancer cells to promote antitumor immunity; it also in situ triggers the cleavage of thermolabile linker at the tumor site to activate the TLR7/8 agonist so as to further potentiate antitumor immune response (Fig. 1b). Such an APC-mediated spatiotemporal potentiation of cancer immunotherapy enables complete eradi- cation of the primary tumor in deep tissue (~8 mm) and efficient inhibition of both distal tumor and lung metastasis without eli- citing obvious systemic adverse effects. Furthermore, the under- lying mechanisms of photothermal activation of immune response along the gradient of photothermal depth and in situ photothermal temperature in the deep beds of tumor are unveiled, providing guidelines for the development of photo- thermal immunotherapy. Results Synthesis and in vitro characterization. To obtain the NIR-II- absorbing semiconducting polymer precursor pBODO-Br, Stille polycondensation was used to copolymerize three monomers: 4,8-bis[5-bromo-4-(2-octyldodecyl)-2-thienyl]-benzo[1,2c:4,5c']bis [1,2,5]thiadiazole (BBT), 2,5-bis(6-bromohexyl)-3,6-bis(5-bro- mothiophen-2-yl)pyrrolo[3,4-c]pyrrole-1,4(2H,5H)-dione (DPP- Br), and (4,8-bis((2-ethylhexyl)oxy)benzo[1,2b:4,5-b'] dithiophene- 2,6-diyl)bis(trimethylstannane) (OT) (Fig. 2a). Because of the strong-electron withdrawing of BBT and the electron-rich OT, PBODO-Br has a charge transfer backbone and narrowed band gap, showing strong absorption in the NIR-II window (Supple- mentary Fig. 1). Gel permeation chromatography analysis indi- cated that pBODO-Br had a number average molecular weight (Mn) of 9826 (Supplementary Fig. 2). pBODO-Br was further transformed to pBODO-N3 through substitution of bromide with azide for post-functionalization (Supplementary Fig. 3). To con- jugate the thermo-responsive linker VA-044 with the immuno- agonist R848, VA-044 was first modified with 7-iodoheptanoic acid, followed by Steglich esterification reaction with R848 to afford caged agonist VR (Supplementary Figs. 4, 5). A bifunctional poly(ethylene glycol) (PEG, Mw=2000) with one propargyl terminal and the other amine terminal (alkyne-PEG-NH2) was synthesized and linked to VR via EDC/NHS coupling to obtain alkyne-PEG-VR conjugate (Supplementary Figs. 6, 7). Thereafter, PBODO-N3 was grafted with alkyne-PEG-VR to afford semi- conducting pro-agonist pBODO-PEG-VR through click reaction (Supplementary Fig. 8). The amphiphilicity of pBODO-PEG-VR allowed its spontaneous assembly in aqueous solution to form nanoparticles termed as APNA (Fig. 1a). To prepare the control nanoparticle without pro-agonist termed as APNC, pBODO-N3 was conjugated with alkyne terminated PEG (pBODO-PEG), fol- lowed by self-assembly in aqueous solution. Optical and colloidal properties of APNA were studied and compared with APNC. Both APNA and APNC had similar absorption spectra with maxima at 690 nm in NIR-I window and 1060 nm in NIR-II window (Fig. 2b), showing that conjugation of pro-agonist had negligible influence on NIR-II light-harvesting property. Whereas dynamic light scattering (DLS) indicated a larger hydrodynamic size of APNA (71 nm) than APNC (48 nm) NATURE COMMUNICATIONS | (2021)12:742 | https://doi.org/10.1038/s41467-021-21047-0 | www.nature.com/naturecommunications NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-21047-0 a N C2H5 C4H9 C2H5 C4H9 R = N=N -N S 0.5 n C8H17 C10H21 0.5 NN C2H5 C4H9 C?H C4H9 NIR-II Photothermal Unit b 0 Photothermal depth (mm) 9 4 7 8 PBODO-PEG-VR i. NIR-II photoirradiation O Primary Tumor Tumor temperature (°C) 50 45 43 42 41 Self- assembly ARTICLE PEG Thermolabile linker Caged agonist ???? NH? ii. Photothermia Immunogenic cell death Photothermal activation TAAS DAMPS (HMGB1, etc.) Inhibition of lung metastasis v. T cell infiltration iv. T cell activation CD8+ T Cell Distant Tumor Abscopal Effect CD4+ T Cell Lymph node iDC Activated agonist iii. DC Maturation Migration MDC Fig. 1 Scheme of APNA-mediated NIR-II photothermal immunotherapy. a Chemical structure of pBODO-PEG-VR and preparation of APNA. b Mechanism of antitumor immune response by APNA-mediated NIR-II photothermal immunotherapy. TAAS tumor-associated antigens, DAMPs damage-associated molecular patterns, iDC immature DC, mDC mature DC, HMGB1 high-mobility group box 1 protein. (Fig. 2c), probably owing to the presence of hydrophobic agonist molecules. Transmission electron microscopy (TEM) further confirmed spherical morphology for both APNA and APNC (Fig. 2c). In addition, zeta potential measurement indicated a relatively neutralized surface charge of APNA (-13 mV) in contrast with APNC (-29 mV) (Supplementary Fig. 9a). Both nanoparticles showed negligible size change during storage in aqueous solutions for 2 months (Supplementary Fig. 9b), suggesting their excellent colloidal stability. According to high performance liquid chromatography (HPLC) calibration curve, the drug loading capacity of APNA was ca. 5.3%, suggesting that each pBODO-PEG-VR molecule contained ~3.3 equivalents of R848 pro-drug. Photothermal property of APNA was evaluated and compared with APNC. Upon continuous NIR-II (1064 nm) photoirradia- tion, both APNA and APNC induced significant temperature rise of aqueous solution (Fig. 2d). After irradiation for 6 min, the maximum solution temperatures of APNA and APNC nanopar- ticles were 78 and 76 °C, respectively. Such phenomenon implied the negligible impact of agonist conjugation on the photothermal transduction capability of semiconducting backbone. Indeed, APNA and APNC had similar photothermal conversion efficiency as high as 84.4% at 1064 nm (Supplementary Fig. 10). In addition, negligible changes in maximal solution temperatures were observed for both APNA and APNC nanoparticles throughout five heating and natural cooling cycles, suggesting their excellent photostability as photothermal agents. Photothermal activation of pro-agonist from APNA was evaluated and analyzed by HPLC (Fig. 2e, f). Without photo- irradiation, no elution peak related to free R848 (TR = 17.9 min) from APNA nanoparticles could be measured (Fig. 2f). After continuous photoirradiation of APNA solution for 10 min, an elution peak at 24.7 min assigned to the released agonist was observed. Such product from the photothermal cleavage was further confirmed by liquid chromatography-mass spectrometry (LCMS) and proton nuclear magnetic resonance spectroscopy ('H NMR) (Supplementary Figs. 11, 12). Through subsequent hydrolysis by esterase, the parent R848 was able to be liberated from the photothermally activated pro-agonist in an intact form, which was validated by both HPLC profiles and LCMS (Fig. 2f, Supplementary Fig. 13). Thereafter, the relationship between photothermal temperature and photothermal activation rate was investigated (Fig. 2g). When the photothermal temperature was kept at 37°C for 20 min under photoirradiation, a maximal agonist activation ratio of 8.5% was achieved. Whereas such ratio was dramatically promoted to 74% when photothermal tempera- ture was elevated to 45 °C or 55 °C and maintained for 20 min. Notably, such high activation ratio was achieved in 5 min with NATURE COMMUNICATIONS | (2021)12:742 | https://doi.org/10.1038/s41467-021-21047-0 | www.nature.com/naturecommunications 3 ARTICLE Absorption a HOOC N NN NEN N ii N=N NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-21047-0 VA-044 VCOOH VR COOH COOH Br C2H5 C4H9 C2H5 C4H9 OT C8H17 C10H21 + N...N S Br S. C8H17 C10H21 DPP-Br Br C2H5 CH9 N NH2 !!! ????? Alkyne-PEG-VR S. N N C2H5C4H9 iv NN -Br N..N C8H17 SC8H17 C10H21 C10H21 N.. N S C10H21 BBT C2H5 C4H9 pBODO-Br Br H?N C2H5C4H9 HK 0. S0.5 n C2H5 C4H9 ?3 vi vii C2H5 C4H9 PBODO-PEG-VR ???? C8H11C10H21 -$0.5 C2H5 C4H9 PBODO-N3 N3 S 0.5 n C2H5 C4H9 b 0.8 ???? APNC 0.6 0.4 0.2 0.0 00 e 600 800 Wavelength (nm) 1064 nm C 25 viii ix PBODO-PEG APNC d 100- APNC ???? 80 Number (%) ???? 20 APNC 15 10 5 APNA APNC 50 nm Temperature (°C) 0 N% 60 40 20 1000 1 10 100 1000 10000 Diameter (nm) Caged agonist R848 APNA - laser ???? Activated agonist H?N APNA + laser H?N R848 Esterase H?N APNA + laser + esterase 0 10 20 Time (min) g 0.8 Drug Release Ratio 0.6 0.4 0.2- 0 720 1440 2160 2880 3600 Time (s) 37 °C 45 °C - 55 °C 0.0 0.0 0 5 10 15 Laser irradiation time (min) 20 Fig. 2 In vitro characterization of APNA. a Synthetic routes of APNA and APNC. (i) 7-iodoheptanoic acid, sodium hydride (NaH), dry tetrahydrofuran (THF), 25 °C, 2d. (ii) R848, 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide (EDC), 4-dimethylaminopyridine (DMAP), dry acetonitrile (ACN), 25 °C, 3 d. (iii) alkyne-PEG-NH2, EDC, N-hydroxysuccinimide (NHS), dry THF, 25 °C, 2d. (iv) Pd2(dba)3, tri(o-tolyl)phosphine, chlorobenzene, 100 °C, 2 h. (v) sodium azide, dimethylformamide (DMF)/THF, 25 °C, 2d. (vi) alkyne-PEG-VR, CuBr, N,N,N',N",N"-pentamethyldiethylenetriamine (PMDETA), dry THF, 25 °C, 2d. (vii) aqueous self-assembly of pBODO-PEG-VR. (viii) methoxy-PEG-alkyne, CuBr, PMDETA, dry THF, 25 °C, 2d. (ix) aqueous self-assembly of pBODO- PEG. b Absorption spectra of APNA and APNC in 1× PBS solution. c DLS profiles of APNA and APNC nanoparticles. Inset: TEM images of APNA and APNC nanoparticles. d Photostability studies of APNA and APNC ([pBODO] = 20 ?g mL ?¹) by photothermal heating (1064 nm photoirradiation, 1 W cm-2, 6 min) and cooling (natural cooling, 6 min) cycles. e Schematic illustration of photothermally triggered agonist release from APNA and subsequent hydrolysis by esterase. f HPLC analysis of photothermally triggered agonist release from APNA ([pBODO] = 50 ?g mL?1). 1064 nm photoirradiation: 1 W cm-2, 10 min. g Relationship of photothermal activation ratio and different photothermal temperatures ([pBODO] = 50 µg mL?1). The photothermal temperature was controlled by switching power density of photoirradiation. Data were expressed as mean ± SD. Error bars indicated standard deviations of three independent measurements. 4 NATURE COMMUNICATIONS | (2021)12:742 | https://doi.org/10.1038/s41467-021-21047-0 | www.nature.com/naturecommunications d NATURE COMMUNICATIONS | https://doi.org/10.1038/s41467-021-21047-0 C a DAPI Lysosome SPN Merge DAPI Lysosome SPN Merge 120 APNAF PBS APNCF 20 ?m - Cell Viability (%) 100- 80 60 60 40 60 APNC - Laser APNA Laser 40 APNC + Laser APNA + Laser 20 20 ?m 0 5 10 ARTICLE 20 50 Concentration (?g mL-1) e PBS R848 APNC - Laser R848 Incubation 105 4.12% 9.57% 105 12.3% 64.1% 105 2.89% 13.7% CD80 CD86 ?t 104- 104- 104- iDC MDC 103- 103- APNA-Laser 103- 0 0 0 CD80 D CD861 80.0% -103 6.27% 21.3% 2.32% 81.4% -103 1.97% -103 iDC mDC -103 0 103 104 105 -103 0 103 104 105 -1030 103 104 105 APNC+Laser APNC + Laser APNA - Laser APNA + Laser CD80 105- 3.13% CD86 20.2% 105- 10.6% 30.1% 105 4.35% 57.5% iDC mDC APNA+Laser CD80 CD86 iDC mDC CD80-FITC 104 104- 104- 103- 103- 103- 0 72.7% 3.94% -103 0 -103 0 56.7% 2.52% 34% 4.18% -103 -103 0 103 104 105 -103 0 103 -103 0 103 104 105 ? CD86-PE 104 105 Fig. 3 In vitro APNA-mediated photothermal immunotherapy. a, b Confocal fluorescence images of cellular internalization (24 h) of APNAF and APNCF ([pBODO] = 10 ?g mL-1) in 4T1 cancer cells a and BMDCs b. APNA and APNC were labeled with NCBS (2.5 w/w%). Blue fluorescence indicated nuclei staining by 4', 6-diamidine-2'-phenylindole dihydrochloride (DAPI). Green fluorescence indicated lysosomes staining by LysoTracker Green DND-26. Red fluorescence denoted as SPN channel indicated NIR fluorescence from APNAF or APNCF. Experiments were performed in triplicate with similar results. c Cell viability assay of 4T1 cells at 12 h after treatment with APNC or APNA at different concentrations with or without 1064 nm photoirradiation (1 W cm-2, 6 min) (n = 3). d Schematic illustration of pre-photothermal activation of APNA and subsequent in vitro stimulation of iDC. e Flow cytometry analysis of BMDC maturation (gated on CD11c+ DCs) at 48 h after various treatments. [R848] = 4.4 µg mL?1; [pBODO] = 10 ?g mL ?1; 1064 nm photoirradiation, 1W cm?², 6 min. Data were expressed as mean ± SD. photothermal temperature at 55 °C, whereas extended to 10 min at 45 °C. These results indicated the agonist could be selectively activated by photothermal heating mediated by the backbone of APNA. In vitro photothermal ablation and DC maturation. Cellular uptake of APNA and APNC was evaluated on 4T1 murine breast cancer cells and bone marrow-derived DCs (BMDCs). A fluor- escent dye (silicon 2,3-naphthalocyanine bis(trihexylsilyloxide)) (NCBS) was doped into nanoparticles (2.5 w/w%) to obtain fluorescent derivatives (APNA and APNCF) (Supplementary Figs. 14, 15). After treating 4T1 cells with APNAF or APNCF for 24 h, strong NIR fluorescence was observed from cellular plasma (Fig. 3a), indicating effective endocytosis of both nanoparticles in 4T1 cells. Similar uptake was detected for BMDCs (Fig. 3b, Supplementary Fig. 16). Furthermore, the nanoparticle signal overlapped well with the green fluorescence from lysosome staining, suggesting that endocytosed nanoparticles mainly resi- ded in lysosomes, wherein TLR7/8 was highly expressed 35,36 Without photoirradiation, both APNA and APNC induced neg- ligible cytotoxicity to 4T1 cells (Fig. 3c). However, with NIR-II photoirradiation, both nanoparticles triggered significant cell death relative to the control group. For instance, at 50 ?g mL the cell viability of APNA and APNC treated-group decreased to 24% and 25%, respectively. ' The ability of APNA to photothermally trigger in vitro immune activation was investigated on DCs, a crucial species of APCs whose maturation impacts the activation of both innate and adaptive immunity37. After photoirradiation of APNA or APNC solution for 10 min, the solutions were transferred to the culture media of immature BMDCs, followed by detection of their maturation by flow cytometry analysis on the expression of the costimulatory molecules CD80 and CD86 (Fig. 3d, Supplementary Fig. 17). The post-photoirradiated APNA triggered upregulation of CD80 and CD86 (57.5%), which was 1.9-fold and 2.8-fold higher than unirradiated APNA (30.1%) or the post- photoirradiated control (APNC) (20.2%) (Fig. 3e). Furthermore, the DC maturation induced by APNA after photothermal activation was similar to free R848 at 4.4 µg mL-¹. Consistently, mixed lymphocyte reaction indicated the superior T-cell stimula- tion capacity of pre-activated APNA-treated DCs, as revealed by the higher percentage of CD3+CD8+ T cells and elevated IFN-y production relative to other groups (Supplementary Fig. 18). These results show that the immune-stimulating ability of APNA was effectively activated by NIR-II photoirradiation. NATURE COMMUNICATIONS | (2021)12:742 | https://doi.org/10.1038/s41467-021-21047-0 | www.nature.com/naturecommunications 5

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Student that preparing to become a mental health counselor Please respond on 4 scenarios with full sentences and correct grammar Scenario 1 Your teenage client is pregnant and does not want to give birth to the baby. In your response, please indicate :1. Why this situation would challenge you (250 words) Because of working as dance instructor for 25 years with kids, and currently working with teenage girls with severe emotional tauma in a private school as a teacher assistant and see a lot of very young girls going thru very hard time, I really loving to helping them it is just very hard to see and feel their pain Having great compassion for live Having trouble to choose between client choose and personal view on the issue Please develop response around this ideas for about 250 words.

The NEW ENGLAND JOURNAL of MEDICINE ORIGINAL ARTICLE Safety and Efficacy of Vadadustat for Anemia in Patients Undergoing Dialysis K.-U. Eckardt, R. Agarwal, A. Aswad, A. Awad, G.A. Block, M.R. Bacci, Y.M.K. Farag, S. Fishbane, H. Hubert, A. Jardine, Z. Khawaja, M.J. Koury, B.J. Maroni, K. Matsushita, P.A. McCullough, E.F. Lewis, W. Luo, P.S. Parfrey, P. Pergola, M.J. Sarnak, B. Spinowitz, J. Tumlin, D.L. Vargo, K.A. Walters, W.C. Winkelmayer, J. Wittes, R. Zwiech, and G.M. Chertow ABSTRACT BACKGROUND Vadadustat is an oral hypoxia-inducible factor prolyl hydroxylase inhibitor, a class The authors' full names, academic of compounds that stimulate endogenous erythropoietin production. METHODS We conducted two randomized, open-label, noninferiority phase 3 trials to evalu- ate the safety and efficacy of vadadustat, as compared with darbepoetin alfa, in patients with anemia and incident or prevalent dialysis-dependent chronic kidney disease (DD-CKD). The primary safety end point, assessed in a time-to-event analysis, was the first occurrence of a major adverse cardiovascular event (MACE, a composite of death from any cause, a nonfatal myocardial infarction, or a non- fatal stroke), pooled across the trials (noninferiority margin, 1.25). A key second- ary safety end point was the first occurrence of a MACE plus hospitalization for either heart failure or a thromboembolic event. The primary and key secondary efficacy end points were the mean change in hemoglobin from baseline to weeks 24 to 36 and from baseline to weeks 40 to 52, respectively, in each trial (non- inferiority margin, -0.75 g per deciliter). RESULTS A total of 3923 patients were randomly assigned in a 1:1 ratio to receive vadadus- tat or darbepoetin alfa: 369 in the incident DD-CKD trial and 3554 in the prevalent DD-CKD trial. In the pooled analysis, a first MACE occurred in 355 patients (18.2%) in the vadadustat group and in 377 patients (19.3%) in the darbepoetin alfa group (hazard ratio, 0.96; 95% confidence interval [CI], 0.83 to 1.11). The mean differences between the groups in the change in hemoglobin concentration were -0.31 g per deciliter (95% CI, ?0.53 to ?0.10) at weeks 24 to 36 and -0.07 g per deciliter (95% CI, ?0.34 to 0.19) at weeks 40 to 52 in the incident DD-CKD trial and -0.17 g per deciliter (95% CI, ?0.23 to ?0.10) and ?0.18 g per deciliter (95% CI, ?0.25 to -0.12), respectively, in the prevalent DD-CKD trial. The inci- dence of serious adverse events in the vadadustat group was 49.7% in the incident DD-CKD trial and 55.0% in the prevalent DD-CKD trial, and the incidences in the darbepoetin alfa group were 56.5% and 58.3%, respectively. CONCLUSIONS Among patients with anemia and CKD who were undergoing dialysis, vadadustat was noninferior to darbepoetin alfa with respect to cardiovascular safety and cor- rection and maintenance of hemoglobin concentrations. (Funded by Akebia Therapeutics and Otsuka Pharmaceutical; INNOVATE ClinicalTrials.gov numbers, NCT02865850 and NCT02892149.) degrees, and affiliations are listed in the Appendix. Address reprint requests to Dr. Eckardt at the Department of Medical Intensive Nephrology and Care, Charité-Universitätsmedizin Berlin, Charitéplatz 1, 10117 Berlin, Germany, or at nephro-intensiv@charite.de. A list of investigators is provided in the Supplementary Appendix, available at NEJM.org. N Engl J Med 2021;384:1601-12. DOI: 10.1056/NEJMoa2025956 Copyright 2021 Massachusetts Medical Society. N ENGL J MED 384;17 NEJM.ORG APRIL 29, 2021 The New England Journal of Medicine Downloaded from nejm.org on May 7, 2024. For personal use only. No other uses without permission. Copyright © 2021 Massachusetts Medical Society. All rights reserved. 1601 1602 The NEW ENGLAND JOURNAL of MEDICINE A NEMIA, A COMMON COMPLICATION OF chronic kidney disease (CKD), is associ- of life, an increase in red-cell transfusions, and a heightened risk of cardiovascular events. 1-3 Erythropoiesis-stimulating agents (ESAs) (i.e., recombinant human erythropoietin and its de- rivatives) are standard care for the management of anemia in patients with CKD. The use of ESAs to target hemoglobin concentrations in the nor- mal or near-normal range in patients with CKD has been shown to increase the risks of stroke, vascular access thrombosis, and death 4-6 ; such findings have resulted in recommendations for caution in the use of ESAs and for only partial correction of anemia. Hypoxia-inducible factor (HIF), a transcription factor that regulates physiological responses to hypoxia, stimulates erythropoietin production by the liver and kidneys. 8-10 HIF is regulated by oxy- gen-dependent proteasomal degradation through a family of prolyl hydroxylases that serve as oxy- gen sensors. 9,¹¹ HIF prolyl hydroxylase inhibitors comprise a recently developed class of com- pounds that stabilize HIF, in turn stimulating endogenous erythropoietin production and ulti- mately erythropoiesis. 10,12-15 Vadadustat, an oral HIF prolyl hydroxylase in- hibitor, is an investigational drug that is in de- velopment for the treatment of anemia associ- ated with CKD. In phase 2 trials, vadadustat was reported to increase and maintain hemoglobin concentrations in patients with CKD and anemia both those who were undergoing dialysis and those who were not undergoing dialysis." 16-19 The vadadustat phase 3 program includes four phase 3 international, randomized, controlled trials: two trials involving patients with non-dialysis-depen- dent CKD (the PROTECT trials) and two trials involving patients with dialysis-dependent CKD (DD-CKD) (the INNOVATE trials). Here, we re- port the results of the two INNOVATE trials, which evaluated the cardiovascular safety and hematologic efficacy of vadadustat as compared with the ESA darbepoetin alfa. METHODS TRIAL DESIGN AND OVERSIGHT Details regarding the rationale, design, and methods of the two INNOVATE trials were de- scribed previously, 20 and the protocols for the trials are available with the full text of this article at NEJM.org. Both trials were randomized, open- were designed to evaluate the cardiovascular safety and hematologic efficacy of vadadustat, as compared with darbepoetin alfa, for the treat- ment of anemia in patients undergoing hemo- dialysis or peritoneal dialysis. In both trials, personnel at Akebia Therapeutics and Otsuka Pharmaceutical were unaware of the treatment as- signments. In the incident DD-CKD trial (correc- tion-conversion trial; ClinicalTrials.gov number, NCT02865850), which involved the correction and maintenance of hemoglobin concentrations, patients were to have initiated dialysis within 16 weeks before screening and were to have had limited exposure to ESAs. In the prevalent DD-CKD trial (conversion trial; NCT02892149), which involved the maintenance of hemoglobin concentrations, patients were to have been under- going maintenance dialysis for at least 12 weeks before screening and were to have been receiving treatment with an ESA.20 Akebia Therapeutics designed the trials and protocols with input from an executive steering committee, and Otsuka Pharmaceutical partici- pated in the executive steering committee meet- ings and provided input on trial protocol amend- ments. An independent ethics committee approved the informed consent forms. The trial investiga- tors conducted the trials in collaboration with Akebia Therapeutics. The executive steering com- mittee supervised the conduct and progress of the trials. The trials were monitored by an inde- pendent data and safety monitoring committee (lists of the members of these committees are provided in the Supplementary Appendix, avail- able at NEJM.org). The first and last authors wrote the first draft of the manuscript and made final decisions regarding the content of the sub- mitted manuscript. All the authors had access to the trial data, critically reviewed earlier drafts of the manuscript, and approved the manuscript for submission. The investigators vouch for the ac- curacy and completeness of the data; the authors and Akebia Therapeutics vouch for the fidelity of the trials to the respective protocols and for the analysis of the data. PARTICIPANTS In both trials, eligible patients were at least 18 years of age, had CKD and were undergoing di- N ENGL J MED 384;17 NEJM.ORG APRIL 29, 2021 The New England Journal of Medicine Downloaded from nejm.org on May 7, 2024. For personal use only. No other uses without permission. Copyright © 2021 Massachusetts Medical Society. All rights reserved. VADADUSTAT FOR ANEMIA IN PATIENTS UNDERGOING DIALYSIS alysis, had a serum ferritin concentration of at least 100 ng per milliliter and a transferrin satu- ration of at least 20%, and had not received a red-cell transfusion within the previous 8 weeks. In addition, patients had a hemoglobin concen- tration between 8 and 11 g per deciliter (incident DD-CKD trial) or a hemoglobin concentration between 8 and 11 g per deciliter (patients in the United States) or between 9 and 12 g per deci- liter (patients in other countries) (prevalent DD-CKD trial). Patients were excluded if they had anemia that was considered to be due to causes other than CKD or if they had uncon- trolled hypertension or had had a recent cardio- vascular event.20 All the patients provided written informed consent. RANDOMIZATION AND TRIAL PERIODS Eligible patients were randomly assigned, in a 1:1 ratio, to receive vadadustat or darbepoetin alfa. Randomization was stratified according to geographic region (United States vs. Europe vs. other regions), New York Heart Association (NYHA) heart failure classification (class 0 or I vs. class II or III), and hemoglobin concentration at trial entry (incident DD-CKD trial, <9.5 vs. ?9.5 g per deciliter; prevalent DD-CKD trial, <10 vs. ?10 g per deciliter). Both trials had four defined trial periods: a correction or conversion period (weeks 0 to 23); a maintenance period (weeks 24 to 52), comprising the primary (weeks 24 to 36) and secondary (weeks 40 to 52) efficacy evaluation periods; a long-term treatment period (weeks 53 to the end of treatment); and a 4-week safety follow-up period.20 END POINTS The primary safety end point, assessed in a time-to-event analysis, was the first occurrence of an adjudicated major adverse cardiovascular event (MACE) ? a composite end point of death from any cause, a nonfatal myocardial infarc- tion, or a nonfatal stroke - pooled across the two trials. Key secondary safety end points, which were also pooled across the trials, were the first occurrence of "expanded MACE" (a MACE plus hospitalization for either heart fail- ure or a thromboembolic event, excluding vas- cular access failure); death from cardiovascular causes, a nonfatal stroke, or a nonfatal myocar- dial infarction combined; death from cardio- vascular causes; and death from any cause. Adjudication of MACE was performed by an independent clinical end-point committee whose members were unaware of the treatment as- signments (a list of the committee members is provided in the Supplementary Appendix). The primary efficacy end point was the mean change in the hemoglobin concentration from baseline to the average concentration during the primary evaluation period, and the key sec- ondary efficacy end point was the mean change in the hemoglobin concentration from baseline to the average concentration during the sec- ondary evaluation period.20 INTERVENTION The starting dose of vadadustat was 300 mg orally once daily, with doses of 150, 450, and 600 mg available for adjustment of the dose to a maximum of 600 mg daily. Darbepoetin alfa was administered subcutaneously or intrave- nously; the initial dose was based on the previ- ous dose or, in the case of patients who had not received darbepoetin alfa before random- ization, on information in the product label. Doses of the trial medications were adjusted ac- cording to protocol-specified dose-adjustment algorithms to achieve target hemoglobin con- centrations (in the United States, 10 to 11 g per deciliter; in other countries, 10 to 12 g per deciliter). 20 We encouraged the use of iron supplementation (intravenous, oral, or intradi- alytic administration) to maintain a serum fer- ritin concentration of at least 100 ng per mil- liliter or a transferrin saturation of at least 20%. The provision of red-cell transfusions did not necessitate discontinuation of the trial med- ication. Starting at week 6, patients in both treatment groups could receive ESAs as rescue therapy if they had worsening symptoms of anemia and a hemoglobin concentration of less than 9.5 g per deciliter. In addition, in the dar- bepoetin alfa group, an ESA was defined post hoc as a rescue medication if the dose was at least double that of the previous dose of darbe- poetin alfa. Patients temporarily discontinued the trial medication while receiving ESAs as rescue therapy. STATISTICAL ANALYSIS The prespecified noninferiority margins, which were selected in consultation with regulatory agencies, were an upper bound of the 95% con- N ENGL J MED 384;17 NEJM.ORG APRIL 29, 2021 The New England Journal of Medicine Downloaded from nejm.org on May 7, 2024. For personal use only. No other uses without permission. Copyright © 2021 Massachusetts Medical Society. All rights reserved. 1603 1604 The NEW ENGLAND JOURNAL of MEDICINE fidence interval of 1.25 for the primary safety end point and a lower bound of -0.75 g per deciliter for the primary efficacy end point. 20 To evaluate the primary and key secondary efficacy end points, an analysis of covariance with mul- tiple imputation for missing data was used, with baseline hemoglobin concentration, geographic region, and NYHA class as covariates. The analy- sis of the time to a first occurrence of a MACE was performed with the use of a Cox regression model stratified according to trial. The model included the following covariates: baseline hemo- globin concentration, geographic region (United States vs. Europe vs. other regions), NYHA class (0 or I vs. II or III), sex, age (?65 years vs. >65 years), race (White vs. non-White), cardiovascu- lar disease (yes vs. no), and diabetes mellitus (yes vs. no). Subgroup analyses were performed with the use of the same Cox model as that used in the primary analysis. PATIENTS RESULTS Across the two trials, 3923 patients underwent randomization: 369 in the incident DD-CKD trial and 3554 in the prevalent DD-CKD trial (Fig. S1 in the Supplementary Appendix). The median duration of follow-up was 1.2 years (in- terquartile range [25th to 75th percentile], 0.8 to 1.7) in the incident DD-CKD trial and 1.7 years (interquartile range, 1.2 to 2.2) in the prevalent DD-CKD trial. patients (18.2%) in the vadadustat group and in 377 of the 1955 patients (19.3%) in the darbepo- etin alfa group (hazard ratio, 0.96; 95% confi- dence interval [CI], 0.83 to 1.11). The numbers and percentages of patients in whom the first MACE was death from any cause, a nonfatal myocardial infarction, or a nonfatal stroke were 253 (13.0%), 76 (3.9%), and 26 (1.3%), respec- tively, in the vadadustat group and 253 (12.9%), 87 (4.5%), and 37 (1.9%), respectively, in the darbepoetin alfa group (Table S2). The results within each trial were qualitatively consistent with the pooled analysis, but the confidence in- terval in the incident DD-CKD trial, which was a much smaller trial than the prevalent DD-CKD trial, was wide (incident DD-CKD trial: hazard ratio of a first MACE, 0.97; 95% CI, 0.54 to 1.76; prevalent DD-CKD trial: hazard ratio, 0.96; 95% CI, 0.83 to 1.12) (Table S3). Figure 1B shows the cumulative probability of a first expanded MACE, which occurred in 420 of the 1947 patients (21.6%) in the vadadustat group and in 449 of the 1955 patients (23.0%) in the darbepoetin alfa group (hazard ratio, 0.96; 95% CI, 0.84 to 1.10). Figures 1C and 1D show the pooled cumulative probability of death from cardiovascular causes (hazard ratio, 0.96; 95% CI, 0.77 to 1.20) and the cumulative probability of death from any cause (hazard ratio, 0.95; 95% CI, 0.81 to 1.12), respectively. Figure S2 shows the cumulative probability of a composite of death from cardiovascular causes, a nonfatal myocar- dial infarction, or a nonfatal stroke (hazard ra- tio, 0.95; 95% CI, 0.80 to 1.14). Table S2 shows similar incidences of MACE, expanded MACE, and their components in the two treatment groups across both trials. The results of pre- specified subgroup analyses of a first occurrence of a MACE and a first occurrence of an expand- ed MACE were consistent across subgroups, as shown in Figure 2 and Figure S3, respectively. The baseline characteristics at randomization have been described previously.20 The demo- graphic, clinical, and laboratory characteristics of the two treatment groups were generally well balanced in both trials (Table 1 and Table S1), except that in the incident DD-CKD trial, the percentage of patients with diabetes mellitus was higher among the patients randomly as signed to receive vadadustat than among those randomly assigned to receive darbepoetin alfa PRIMARY, KEY SECONDARY, AND OTHER EFFICACY (58.0% vs. 51.1%). PRIMARY AND KEY SECONDARY SAFETY END POINTS Analyses of the safety end points were based on the pooled safety population, which included 1947 patients in the vadadustat group and 1955 patients in the darbepoetin alfa group. Figure 1A shows the cumulative probability of a first MACE. A first MACE occurred in 355 of the 1947 END POINTS Incident DD-CKD Trial The median doses of vadadustat and darbepoetin alfa over the course of the trial are shown in Figure S5. Figure 3A shows the mean changes in hemoglobin concentrations in the two treat- ment groups over time. The least-squares mean (±SE) change in hemoglobin concentration from baseline to the average of the values during N ENGL J MED 384;17 NEJM.ORG APRIL 29, 2021 The New England Journal of Medicine Downloaded from nejm.org on May 7, 2024. For personal use only. No other uses without permission. Copyright © 2021 Massachusetts Medical Society. All rights reserved. VADADUSTAT FOR ANEMIA IN PATIENTS UNDERGOING DIALYSIS Table 1. Selected Demographic, Clinical, and Laboratory Characteristics of the Patients at Baseline in the Randomized Populations.* Incident DD-CKD Trial Prevalent DD-CKD Trial Characteristic Vadadustat (N=181) Darbepoetin Alfa (N=188) Vadadustat (N=1777) 56.5±14.8 55.6±14.6 57.9±13.9 Darbepoetin Alfa (N=1777) 58.4±13.8 Age - yr Male sex no. (%) 107 (59.1) 113 (60.1) 990 (55.7) 1004 (56.5) Racial or ethnic group ? no. (%)† 129 (71.3) 143 (76.1) 1135 (63.9) 1096 (61.7) White 38 (21.0) 35 (18.6) 432 (24.3) 444 (25.0) Black 12 (6.6) 8 (4.3) 76 (4.3) 99 (5.6) Asian American Indian 1 (0.6) 0 19 (1.1) 30 (1.7) 0 0 13 (0.7) 6 (0.3) Native Hawaiian 0 1 (0.5) 42 (2.4) 45 (2.5) Other group Multiple groups 1 (0.6) 0 8 (0.5) 5 (0.3) 0 1 (0.5) 52 (2.9) 52 (2.9) Not reported Hispanic ethnic group — no. (%)† Hispanic Non-Hispanic 71 (39.2) 66 (35.1) 682 (38.4) 674 (37.9) 104 (57.5) 118 (62.8) 1043 (58.7) 1040 (58.5) Not reported Unknown Time since dialysis initiated Type of dialysis — no. (%) - 5 (2.8) 3 (1.6) 36 (2.0) 47 (2.6) 1 (0.6) 1 (0.5) 16 (0.9) 0.14±0.09 0.15±0.28 4.00±4.02 16 (0.9) 3.94±4.01 - yr In-center hemodialysis 158 (87.3) 169 (90.9) 1652 (93.0) 1633 (91.9) Peritoneal dialysis 22 (12.2) 16 (8.6) 137 (7.7) 143 (8.0) Unknown or combination 3 (1.7) 1 (0.5) 17 (1.0) 18 (1.0) Disease history- — no. (%) Diabetes mellitus 105 (58.0) 96 (51.1) 971 (54.6) 998 (56.2) Cardiovascular disease 69 (38.1) 73 (38.8) 868 (48.8) 932 (52.4) Hemoglobin concentration - g/dl 9.4±1.1 9.2±1.1 10.6±0.9 10.2±0.8 * Plus-minus values are means ±SD. Percentages may not total 100 because of rounding. DD-CKD denotes dialysis- dependent chronic kidney disease. * Racial and ethnic groups were reported by the patient. *This analysis was performed in the safety population in both trials. Patients could have been included in more than one category. weeks 24 to 36 was 1.26±0.11 g per deciliter in the vadadustat group and 1.58±0.11 g per deci- liter in the darbepoetin alfa group. The corre- sponding changes from baseline to the average of the values during weeks 40 to 52 were 1.42±0.13 g per deciliter and 1.50±0.14 g per deciliter, respectively. The mean (±SE) differ- ences between the groups in the change in hemo- globin concentration were ?0.31±0.11 g per deci- liter (95% CI, ?0.53 to -0.10) at weeks 24 to 36 and ?0.07±0.13 g per deciliter (95% CI, -0.34 to 0.19) at weeks 40 to 52. The percentages of patients who had an aver- age hemoglobin concentration within their country-specific target range during weeks 24 to 36 were 43.6% in the vadadustat group and 56.9% in the darbepoetin alfa group. During weeks 40 to 52, the percentages were 39.8% and 41.0%, respectively (Table S5). The percentages of patients who received red- cell transfusions during weeks 24 to 36 were 1.3% in the vadadustat group and 1.8% in the darbepoetin alfa group. During weeks 40 to 52, the percentages were 2.4% and 0.7%, respectively. N ENGL J MED 384;17 NEJM.ORG APRIL 29, 2021 The New England Journal of Medicine Downloaded from nejm.org on May 7, 2024. For personal use only. No other uses without permission. Copyright © 2021 Massachusetts Medical Society. All rights reserved. 1605

INSTRUCTIONS Data is given in the document There are 51 questions you don't need to answer them, you will do the lab report only and you will provide the graphs and the anova results You have to do it as per the rubric and provide the reference as well Experiment is about barb fish - it is also mentioned in the document Student note The two figures also should be included in the report under results section and with a description underneath as in the rubric Need outside references and cannot use the introduction section which is in the document/n Methods Information Worksheet Fill out the following information as best that you can for your study. Not every question will be applicable to your specific experiment or study system, especially if you are doing a field study. Depending on how prepared you are to begin your experiment, you may not be able to fill out all of this information today-remember to come back to anything you skipped and fill it out later! If you run into anything you're not 100% sure about, ask your TA or lab coordinator so that they can help you finalize your experiment. Keep this sheet to use as a reference later when you go to write your rough draft and final paper. Holes closer to front KIA CELL: 9163173526 STEPH CELL: Standard error of median: 1.253 x SEM Stress behaviors: average of stress behaviors for all treatment groups in a bar graph: error bars for standard error of mean Discussion section: reliability include multiple replicates of demonstrators that could tell us the tank of demonstrators was particularly good or bad and then take the average between those tanks for a more accurate view for how the fish learn; restraints of class Median Maze Completion Time of School (s) 300 270 240 210 180 150 120 90 60 30 0 1 2 3 4 5 6 7 8 9 10 11 12 Trial Number 13 14 Excel data below ?Control 25% demonstrators 37.5% demonstrators 50% demonstrators 1 of 19 SE SE median 300 12.569805 4.189935 5.2499886 300 9.1923882 3.0641294 3.8393541 216 48.843043 16.281014 20.400111 50 4.1382363 1.3794121 1.7284034 31 13.287346 4.4291154 5.5496816 36 10.273927 3.4246423 4.2910768 47 92.642843 30.880948 38.693828 80.5 139.13553 46.378511 58.112274 110.5 93.321162 31.107054 38.977139 45.5 116.35874 38.786248 48.599168 41.5 124.62744 41.542482 52.052729 25 127.61298 42.537658 53.299686 39.5 118.86607 39.622024 49.646396 87.5 80.002567 26.667522 33.414405 16.5 8.5596645 2.8532215 3.5750866 15 8.0256286 2.6752095 3.3520375 7 12.339686 4.1132288 5.1538756 6.5 11.236897 3.7456324 4.6932774 9.5 10.82243 3.6074768 4.5201684 4 9.3808315 3.1269438 3.9180606 3.5 3.3990545 1.1330182 1.4196718 145.5 42.473311 14.15777 17.739686 76.5 78.74178 26.24726 32.887817 154 51.920097 17.306699 21.685294 133.5 65.130501 21.710167 27.202839 41.5 29.594582 9.8648607 12.36067 21.5 46.909487 15.636496 19.592529 48.5 18.258071 6.0860235 7.6257875 24.5 10.69045 3.5634832 4.4650445 treatment gro? Median time stdev control control control control control control control control control control control control control control 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.375 0.375 0.375 0.375 0.375 0.375 0.375 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 17.5 0.5 0.5 0.5 0.25 0.25 0.25 0.25 0.25 0.25 0.25 0.375 0.375 0.375 0.375 0.375 0.375 0.375 13 15.175168 5.0583892 6.3381617 9.5 18.703991 6.2346637 7.8120336 12.5 33.613082 11.204361 14.039064 10.5 40.530192 13.510064 16.92811 7.5 101.56903 33.856343 42.421998 17 67.811582 22.603861 28.322638 9.5 1.407886 0.4692953 0.588027 11 11.389218 3.796406 4.7568967 8 28.154865 9.384955 11.759349 16.132819 5.3776064 6.7381408 24 10.514446 3.5048153 4.3915335 19.5 19.398085 6.4660284 8.1019336 38.5 51.135674 17.045225 21.357666 4.5 21.293862 7.0979541 8.8937365 5.5 6.4972522 2.1657507 2.7136857 5 1.1649647 0.3883216 0.4865669 4 1.3887301 0.46291 0.5800263 3 1.0350983 0.3450328 0.4323261 1.5 6.0812945 2.0270982 2.539954 3 15.609063 5.2030211 6.5193854 17 1.5059406 0.5019802 0.6289812 10.5 14.33278 4.7775932 5.9863243 8 8.5178384 2.8392795 3.5576172 8.5 39.376389 13.125463 16.446205 62 35.894438 11.964813 14.99191 16.5 29.061511 9.6871704 12.138024 74 14.297228 4.7657425 5.9714754 2 of 19 12 10 8 ||.|| 0 Control 25% Demonstrators 37.5% Demonstrators 50% Demonstrators Treatment Group treatmemt grou Mean behavio STDEV Control 25% Demo 3.9285714 1.7743595 37.5% Demo 8.7857143 3.9258232 50% Demor 7.5714286 3.1061796 9.2142857 2.5773741 SE 0.6965876 0.4795566 1.0610333 0.839508 3 of 19 Oneway Anova Summary of Fit Analysis of Variance Sum of Source DF Squares Mean Square fish 3 83064.14 Error 52 161242.71 27688.0 3100.8 8.9293 F Ratio Prob > F <.0001* C. Total 55 244306.86 ? Means for Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 0.5 14 17.143 14.882 -12.72 47.01 0.25 14 7.214 14.882 -22.65 37.08 0.375 14 60.929 14.882 31.06 90.79 control 14 104.143 14.882 74.28 134.01 Std Error uses a pooled estimate of error variance Means Comparisons ? Comparisons for all pairs using Tukey-Kramer HSD ? Confidence Quantile ? HSD Threshold Matrix ? Connecting Letters Report Ordered Differences Report Level - Level Difference Std Err Dif control 0.25 0 50 100 150 96.92857 21.04696 41.0679 control 0.5 87.00000 21.04696 31.1393 Lower CL Upper CL p-Value 152.7893 0.0002* 142.8607 0.0007* 0.375 0.25 53.71429 0.375 0.5 43.78571 21.04696 21.04696 -2.1464 109.5750 0.0636 -12.0750 99.6464 0.1730 control 0.375 43.21429 21.04696 -12.6464 99.0750 0.1822 0.5 0.25 9.92857 21.04696 -45.9321 65.7893 0.9650 4 of 19 Oneway Anova Summary of Fit Rsquare 0.348216 Adj Rsquare 0.310613 Root Mean Square Error 2.951764 Mean of Response Observations (or Sum Wgts) ? Analysis of Variance 7.375 56 Sum of Source DF Squares Mean Square fish ratio 3 242.05357 Error 52 453.07143 80.6845 8.7129 F Ratio Prob > F 9.2603 <.0001* C. Total 55 695.12500 Means for Oneway Anova Means Comparisons Comparisons for all pairs using Tukey-Kramer HSD ? Confidence Quantile HSD Threshold Matrix ? Connecting Letters Report ? Ordered Differences Report Level - Level Difference Std Err Dif control 0.25 5.285714 1.115662 0.375 0.25 4.857143 1.115662 0.5 0.25 3.642857 1.115662 0.68178 6.603934 0.0101* control 0.5 1.642857 1.115662 -1.31822 4.603934 0.4611 0.375 0.5 1.214286 1.115662 -1.74679 4.175363 0.6981 control 0.375 0.428571 1.115662 -2.53251 3.389649 0.9805 Lower CL Upper CL p-Value -20 2 4 6 8 2.32464 1.89607 8.246792 <.0001* 7.818220 0.0004* Part 1: Study system 1. What is the scientific name of your animal(s)? ? Puntius Tetrazona (Tiger Barbs) 2. Are you testing other phenotypes, strains, or hybrids than just the wild type? If so, list the phenotypes/strains/hybrids you will be using. ? No, only Wild type 3. How many individuals will you test of each phenotype/strain/hybrid, including the wild type? We have a total of 24 tiger Barbs 5 of 19

REQUEST FOR PROPOSALS (RFP) GLOBAL AND REGIONAL ENVIRONMENTAL CHANGE PROGRAM An Application Guide West Virginia University Biology 321 Science Foundation BSF-24-1 January 2024 Open Invitation To Submit Proposals January 1, 2024 Dear Scientist, Thank you for your interest in the Biology Science Foundation's Global and Regional Environmental Change Program. The West Virginia University Biology Science Foundation (BSF) is a pseudo-government agency founded in 1993. The Foundation was created by the staff of Biology 321. Its aim is to promote and advance knowledge of pressing problems in environmental and evolutionary biology. BSF welcomes proposals on behalf of all qualified Biology 321 students. Awardees are wholly responsible for conducting their project activities and preparing the results for publication. This packet contains five items to assist you in your proposal preparation: (1) the program announcement (describing the needs of the program), (2) guidelines for preparation of pre- proposals, (3) guidelines for preparation of proposals, (4) proposal review procedures and criteria, (5) appendices (containing standard forms to be used for the proposal cover sheet and budget). We look forward to receiving your pre-proposals and proposals! Sincerely, Kevin J. Barry BSF Program Director Associate Program Directors: Cameron Corbett Hannah DeHetre Emel Kangi Table of Contents I. II. III. IV. PROGRAM ANNOUNCEMENT PROPOSAL OUTLINE GUIDELINES GUIDELINES FOR PREPARATION OF PROPOSALS PROPOSAL REVIEW I. Program Announcement Ecology is the study of the relationship of organisms to their natural environments, including physical factors and other organisms. On global and regional scales, one species is having inordinately large effects on the rest. That species is Homo sapiens. Environmental change wrought by H. sapiens is occurring on a scale not seen since the extinction of the dinosaurs 65 million years ago. In essence, our species is performing one giant, uncontrolled experiment on the globe. Many fear drastic consequences of this experiment. Indeed, the evidence is already mounting that drastic consequences have already occurred (an iceberg the size of Rhode Island breaking off in Antarctica!), but that these may be only the tip of the iceberg (no pun intended!). For example, acid rain, in combination with pollutants, has undoubtedly been responsible for decimation of the majestic forests of eastern Europe and depletion of the formerly trout-filled streams of the Adirondack Mountains of New York. Chlorofluorocarbons (CFCs) are causing a breakdown of the ozone layer and this has already shown up over Antarctica and the Arctic as a "hole" in the atmosphere through which damaging ultraviolet radiation can penetrate. Burning of fossil fuels has led to increases in atmospheric carbon dioxide from ca. 270 ppm (parts per million) in the mid-1800s to 400 ppm now, and meteorological, geological and oceanographic data point to global warming over the past few decades. Numerous more regional and localized environmental changes are occurring as well and will affect ecosystems, communities, populations and individuals in important ways. We have only begun to investigate what effect these environmental changes will have on the rest of the species with whom we share this planet. This is where the science of ecology comes in. Of prime importance is the effect on plants because plants are the "engines" of the world's ecosystem - they take the energy in sunlight and, through photosynthesis, incorporate it into the biosphere, thus "driving" the rest of the ecosystem. Thus, if plants are adversely affected by global or regional environmental change, the rest of the system cannot help but be affected as well. Over the past decade many studies of single factor effects on certain species of plants and animals have been performed. For example, many studies have asked “How will plants respond to a doubling of CO2 in the atmosphere?” However, increasingly ecologists are finding that the response of different species or genotypes to a given factor may differ. For example, do the effects of elevated CO2 differ for C-3 species and C-4 species? Or, does the effect of acid precipitation differ for spruce trees vs. pine trees? Moreover, ecological geneticists ask whether the effects of an environmental variable depend on the genotype. Effects of a factor may also depend on the levels of another factor - in other words, for a given species, 2 factors may show a dependency on the levels of each other; an ‘interaction', in a statistical sense. For example, does the effect of CO2 depend on the level of acid precipitation? Why? At a high CO2 level, a plant may gain more carbon through photosynthesis and be better able to withstand the negative effects of acid precipitation than when CO2 levels are low. All of these examples show that we cannot readily predict the consequences of global or regional environmental change without explicitly designing experiments that includes different species or genotypes, or examine two-factor effects on a species. Proposed studies should address the possible importance of two-way interactive effects (species x factor, genotype x factor, or factor x factor). The BSF is interested in supporting research using either model systems OR representatives of native species for which environmental change is a particular concern. It will not be possible to work with vertebrate species due to animal care protocol requirements which cannot be met in the time-frame of this course. Within these broad parameters, investigators are free to propose a study of virtually any environmental factor(s) changing or presenting a stress in the present environment for certain organisms. Your research advisor may narrow your choices slightly by choosing a 'theme' for your lab section. Priority will be given to those proposals that have an explicit and well-thought-out rationale for examining particular species, genotypes, or factors. Investigators are particularly encouraged to use well- chosen 'species' or 'genotypes' as one of the factors. Please see proposal review criteria for further details on how to maximize your chances of funding. II. Proposal Outline Guidelines A. Format Proposal outlines should be comprised of a one-page description of your planned project, including: (A) Tentative Title of proposal (B) Names of Principal Investigators (P.I.s); Triad #; Name of TA (C) Statement of the question being addressed (D) Statement of why this question is important (E) What species (or community or soil or ecosystem) will you use as your experimental system? (F) List the independent variables (i.e., 'factors') in your experiment (G) List the planned 'levels' of each factor (H) List the dependent variables you plan to measure on your target organism (or system) (I) State what the implications of your findings could be (J) Seed germination / plant propagation requirements. (K) References; give at least one reference on your topic from the scientific literature B. Criteria for judging proposal outlines. •Title should adequately describe the project, including the factors and organism/system to be investigated. •Names of P.I.s/TA/Triad Number should be included. •Question statements. The questions should clearly address the potential for an interactive effect' between the two factors being varied in the experiment. 10 pts •The 'Why Is This Important' justification for the question. It should be clear how the question addresses a novel problem and why the question is an interesting one. 10 pts. •Experimental system/species. The species to be used must be (a) practical for experimental study, (b) affordable for TSE program, (c) easy to cultivate/grow/raise, (d) relevant to the question being addressed. 10 pts. •Independent variables. Two. It must be possible to manipulate them independently. They must be practical for inexpensive manipulation. They must not be dangerous or require special or expensive conditions. 10 pts. •Levels of each factor. Chosen for a reason. Span a range that may be expected to have biological effects. 10 pts. •Dependent variables. Do-able using the equipment/facilities available. Meaningful in terms of addressing the question. Practical for the organism/system of choice. 10 pts. •Significance. What are the potential implications of your expected findings? Show thought about what inferences could be made with alternative possible outcomes. 10 pts. •Seed germination / plant propagation requirements. Must explain germination /propagation process, requirements, and timeline. 10 pts. •References. Must list one scientific reference on the chosen topic. 10 pts./n Background/Introduction citations https://www.sciencedirect.com/science/article/abs/pii/B9781893997943500209 - discusses nutritional uses of sunflowers, such as benefits of sunflower oils https://www.annualreviews.org/doi/full/10.1146/annurev.environ.041008.093740 - discusses the importance of crop yield maximization as well as the importance of focusing on crop yield in the future due to growing populations https://acsess.onlinelibrary.wiley.com/doi/epdf/10.2134/agronj1988.00021962008000050 017x - Focuses on how light affects the growth of sunflower plants https://link.springer.com/chapter/10.1007/978-0-387-77594-4_6 - States the importance https://aocs.onlinelibrary.wiley.com/doi/epdf/10.1007/BF02582585 - Sunflower use in https://www.mdpi.com/2311-7524/9/10/1079 - use of sunflowers in biofuel https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8069385/ - introduction states that sunlight levels vary longitudinally and there is shorter sunlight duration in northern countries of sunflowers in world trade America https://www.annualreviews.org/doi/pdf/10.1146/annurev.py.30.090192.002525?casa_toke n=i-pF2b-zF34AAAAA%3ARJSwj_bsCK-ExJ7K6i47XtV9y8AAOVgM7mDg8C0VxyZ -yeKCOa-uPcAGh1EWm2MtKTBNThlq02w - says sunflowers are grown worldwide Introduction- MOHAMMAD Sunflower agricultural uses (sunflower oil, etc.) Issues of overpopulation and the need to maximize crop yields How sunlight varies by region and sunflowers are found in lots of regions Identifying how sunlight varies by region can help us to show why we chose sunlight as a factor; using light levels to mimic different regions with their varying levels of sunlight can help us understand how to maximize densities of sunflowers in different regions Background-GROUP EFFORT Sunflower growth stages, regions of the world, and agricultural uses https://link.springer.com/chapter/10.1007/978-1-4614-0356-2_4 - article all about sunflowers (history, background, growth, physical appearance, etc.) Related experiments on sunflower reactions to light and density (find similar studies) https://iopscience.iop.org/article/10.1088/1755-1315/752/1/012019/pdf - discusses changes in growth in sunflowers as a result of varying levels of light https://cdnsciencepub.com/doi/pdf/10.4141/cips84-084 - discusses changes in growth in sunflowers as a result of varying densities Objectives/Questions/Hypotheses- MAYA Research Plan- ABBY Number each pot 1-15 for each testing group (sunlight low density, sunlight high density, shade low density, shade high density) Put 60% shade cloths over shaded test groups Chose 60% to ensure that some sunlight still reached the plants, but enough was restricted to see adequate differences https://eyouagro.com/blog/greenhouse-shade-cloth-guide/ - talks about shade cloth percentages and when they should be used – make sure this is a reputable source Water once a week (amount not yet determined) - same amount for each sample Check weekly height and SPAD reading for 5 plants in each testing group (ruler measured in centimeters and SPAD meter) Use random number generator in week 1 to determine plants being tested to avoid bias - conduct weekly checks on these plants only in concurrent weeks to keep consistency (reduces risk of human error due to high number of samples) Height and SPAD readings will be averaged in pots containing four seedlings Citation on how SPAD readings are good indicators of photosynthesis rates https://acsess.onlinelibrary.wiley.com/doi/abs/10.2135/cropsci1995.00111 83X003500050025x?casa_token=UyhklMequ0QAAAAA:lAgiPV56Heeu QyK-s15mwjnMJxP_-6H1UBDjqfHeSz7YlnKWZ0BChejNpgihqN0uk00 nNmxAaulIrg At end of experiment, place tester plants in drying chamber and take average dry biomass of each of the five samples from each testing group (pots with four plants will be averaged to compare to pot with single plant) - ensures latent water does not modify our results Compare average dry biomass and weekly height and SPAD readings from each group Conduct p-test and determine statistical significance of results Expected Significance- TROY Seed Germination/Propagation- GROUP EFFORT/nNeed to do only Introduction part in 600-700 words double spaced Student name is MOHAMMAD Introduction- MOHAMMAD - Sunflower agricultural uses (sunflower oil, etc.) Issues of overpopulation and the need to maximize crop yields How sunlight varies by region and sunflowers are found in lots of regions - Identifying how sunlight varies by region can help us to show why we chose sunlight as a factor; using light levels to mimic different regions with their varying levels of sunlight can help us understand how to maximize densities of sunflowers in different regions Note from professor : Mohammad, We all picked sections to do and we figured introduction should be the most general so it should be the easiest to do having not been here. On ecampus there is a file labeled request for proposals under week 1 that has most of the information that you will need. If you have any questions or anything just let us know