Additionally, some lymph nodes were disrupted by tumor cells (Figure 4). Figure 4 Distribution characteristics of lymph node this website micrometastasis. A. Marginal sinus type, nonclustered (×400); B. Marginal sinus type, clustered (×200); C. Intermediate sinus type, clustered and nonclustered (×100); D. Parenchymal type, clustered

(×100); E. Diffuse type, clustered (×100); F. Isolated tumor cells (×400). In total, 697 lymph nodes in 45 gastric adenocarcinomas patients were examined, with a median number of 13 nodes (ranging from seven to 46) and an average number of 15. In all, lymph node micrometastasis was identified in 35 of 45 patients and in 242 of 697 nodes (MLR = 34.7%, 242/697). All these nodes showed positive CK immunohistochemical staining. Furthermore, lymph nodes micrometastasis was identified by CK immunohistochemical staining in four of 10 nodes with N0 determined by HE staining. Lymph node micrometastasis was also identified in 61 of 455 (13.4%) lymph nodes with negative CK immunohistochemical staining. The MLR determined by CK staining was 43.5% (303/696). Notably, the MLR determined by HE staining and CK staining showed a significant difference (P = 0.001) (Table 4). Whether identified by HE or CK staining, the MLR was related to lymph

vessel invasion and the depth of invasion (P < 0.05) (Table 5), but was not related to gender, Ganetespib price Lauren classification, type of histology, and blood vessel invasion. Table 4 Patients with lymph node metastasis selleck compound detected by HE and CK staining.   Lymph node metastasis Case

No (%) P Lymph node metastasis LN No (%) P   Positive Negative   Positive Negative   HE 35 (77.8) 10 (22.2) 0.25 303 (43.5) 394 (56.5) 0.001 CK 39 (86.7) 6 (13.3)   242 Osimertinib mw (34.7) 455 (65.3)   Table 5 Correlation between MLR grades and clinical characteristics. Characteristics Samples MLR classification (HE)     P MLR classification (CK)     P     MLR1 MLR2 MLR3   MLR1 MLR2 MLR3   Total 45 10 12 23   6 9 30   Gender         0.607       0.508    Male 26 4 11 11   2 6 18      Female 19 6 1 12   4 3 12   Lauren type         0.823       0.870    Intestinal type 42 9 12 21   6 8 28      Diffuse type 3 1 0 2   0 1 2   Type of histology         0.808       0.833    1–2 28 5 10 13   3 7 18      3 17 5 2 10   3 2 12   Lymphatic vessel invasion         0.000       0.000    Negative 10 9 1 0   5 4 1      Positive 35 1 11 23   1 5 29   Blood vessel invasion         0.086       0.069    Negative 35 10 9 16   6 8 21      Positive 10 0 3 7   0 1 9   Depth of invasion         0.045       0.019    pT1–2 15 6 4 5   5 3 7      pT3–4 30 4 8 18   1 6 23   Discussion The prognosis was significantly related to pathological characteristics. MLR is a simple and effective marker that can prevent stage migration. Nonetheless, the criteria of MLR classification need to be established [9, 10].

Probes (NEO and TAP) were amplified (oligonucleotides listed in Additional file 8 – Table S5) and radioactively labeled with α-[P32]-dCTP (10 μCi/μl; 3,000 Ci/mmol) (Amersham Biosciences) using the Nick Translation System (Invitrogen), according to the manufacturer’s instructions. Real-time RT-PCR Total RNA was extracted from 1 × 108 cells by RNeasy Kit (Qiagen, Hilden, Germany) according to manufacturer’s

instructions. Single strand cDNA was obtained as follows: 1 μg of RNA and 1 μM oligo dT were mixed and incubated for 10 min at 70°C. Then, 4 μl of Improm-II buffer (Promega, Madison, USA), 3 mM MgCl2, 0.5 mM each dNTP, 40 U RNaseOUT (Invitrogen) and 2 μl Improm-II Reverse Transcriptase (Promega)

GSK1838705A were mixed in a final volume of 20 μl and incubated for 2 h at 42°C. The product was then purified with Microcon(r) YM-30 (Millipore, Massachusetts, USA) and resuspended with water at the concentration of 2 ng μl-1. PCR reactions included 10 ng or 0.4-50 ng (standard curve) of single strand cDNA samples as template, 0.25 μmol of each oligonucleotide, H2B histone oligonucleotides for normalization (listed in Additional file 8 – Table S5) and SYBR(r) Green CCI-779 PCR Master Mix (Applied Biosystems, Foster City, USA). A sample from T. cruzi wild type was used as a negative control. The reactions were Selleck GNS-1480 performed and the standard curve was determined in triplicate and all PCR runs were carried out in an Applied Biosystems 7500 Real-Time PCR System. Data was acquired with the Real-Time PCR System Detection Software v1.4 (Applied Biosystems). Analysis was performed using an average of three quantifications for each sample. Western blot analysis For immunoblotting analysis, cell lysates (from 5 Farnesyltransferase × 106 parasites or, for TAP procedures, 5 to 15 μg of total protein and

25-50% of the digestion) were separated by SDS-PAGE using 13% polyacrylamide gels. Protein bands were transferred onto a nitrocellulose membrane (Hybond C, Amersham Biosciences) according to standard protocols [50]. Nonspecific binding sites were blocked by incubating the membrane for 1 h in 5% nonfat milk powder and 0.1% Tween-20 in TBS, pH 8.0. The membrane was then incubated for 1 h with either the monoclonal antibody anti-GFP (3.3 μg ml-1) (Molecular Probes(r) – Invitrogen), monoclonal anti-histidine (1.4 – 2.8 μg ml-1) (Amersham Biosciences), monoclonal anti-c-myc clone 9E10 (10 μg ml-1) (Clontech) or polyclonal serum anti-CBP (1:1,000) (Upstate(r)-Millipore) antibodies. For TAP procedures, polyclonal serum anti-L26 ribosomal protein [51] (1:250) and anti-α2 20S proteasome subunit (1:600) were used. The membrane was washed three times in TBS and was then incubated for 45 min with the secondary antibodies diluted in blocking solution.

Consent Written informed consent was obtained from the parent of the 6 year

old and other patients. Conflict of interests The authors declare that they have no competing interests. References 1. Langley RL: Fatal animal attacks in North Carolina over an 18-year period. C59 in vivo Am J Forensic Med Pathol 1994, 15:160–7.PubMedCrossRef 2. Langley RL, Hunter JL: Occupational fatalities due to animal-related events. Wilderness Environ Med 2001, 12:168–74.PubMedCrossRef 3. Durrheim DN, Leggat PA: Risk to tourists posed by wild mammals in South Africa. J Travel Med 1999, 6:172–9.PubMedCrossRef 4. Bashir MO, Abu-Zidan FM: Motor vehicle collisions with large animals. Saudi Med J 2006, 27:1116–20.PubMed 5. Bury D, Langlois N, Byard RW: Animal-Related Fatalities–Part I: Characteristic Autopsy Findings and Variable Causes of Death Associated with Blunt and Sharp Trauma. J Forensic Sciences 2011, 1556–4029. 6. Vogel JS, Parker JR, Jordan FB, Coury TL, Vernino AR: Persian leopard (Panthera pardus) attack in Oklahoma: case report. Am J Forensic Med Pathol 2000, 21:264–9.PubMedCrossRef

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antimicrobial susceptibility testing BTSA1 mw guidelines. Clin Microbiol Infect 2013, 19:E59-E71.PubMedCrossRef 20. Lestari ES, Severin JA, Filius PM, Kuntaman K, Offra Duerink D, Hadi U, Wahjono H, Verbrugh HA: Comparison of the accuracy of disk diffusion zone diameters obtained by manual zone measurements to that by automated I-BET151 nmr zone measurements to determine antimicrobial susceptibility. J Microbiol Methods 2008, 75:177–181.PubMedCrossRef 21. European Committee on Antimicrobial Susceptibility Testing: Reading guide. Version 2.0. http://​www.​eucast.​org/​fileadmin/​src/​media/​PDFs/​EUCAST_​files/​Disk_​test_​documents/​Reading_​guide_​v_​2.​0_​EUCAST_​Disk_​Test.​pdf (18th December

2012, date last accessed) Competing interests This work Thiamet G was supported by the University of Zurich. There are no competing interests to declare. Authors’ contributions MH conceived of the study, performed the statistical analysis, and drafted the manuscript. RZ participated in data documentation and analysis. ECB, and participated in the study design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.”
“Background Proteins posttranslationally modified by covalent lipid attachment are present in eukaryal and bacterial organisms. In bacteria, 1–3% of the genome encode for lipoproteins. Bacterial lipoproteins are anchored in the membrane surface where they fulfill various cellular functions, ranging from cell wall integrity, secretion, nutrient uptake, environmental signaling to virulence [1–3].

These data are not supportive of a hypothesis that PPIs modify the quality or quantity of bone. The FDA review considered that the biological mechanisms for an increased risk of fractures with PPIs are not known. Despite this, the FDA review concluded that the available data suggested a possible increased risk of fractures with PPI use. In our view, evidence for drug effects should not be used on an assessment

of deviations of summary RRs from unity but rather on an assessment on whether specific hypotheses of biological mechanisms of drug effects are supported by evidence. Given the weak and conflicting evidences, not only from epidemiological studies, but also for a pharmacological effect of PPIs on bone mineral density in humans, we feel that the label change of PPIs is premature. Conflicts of interest The Department of Pharmacoepidemiology and LY3023414 Clinical Histone Acetyltransferase inhibitor Pharmacology, Utrecht Institute for Pharmaceutical Sciences, has received unrestricted research funding from the Netherlands Organisation for Health Research and Development (ZonMW), the private–public funded Top Institute Pharma (www.​tipharma.​nl, includes co-funding from universities, Thiazovivin cost government and industry), the EU Innovative Medicines Initiative, the Dutch Medicines Evaluation Board, the Dutch Ministry of Health and GlaxoSmithKline. GPRD is owned

by the UK Department of Health and operates within the Medicines and Healthcare products Regulatory Agency (MHRA). GPRD is funded by the MHRA, Medical Research Council, various universities, contract research organisations and pharmaceutical companies. HGML is Chair of the Dutch Medicines Evaluation Board and co-opted member of the Committee for Medicinal

Products for Human Use of the European Medicines Agency in London, United Kingdom. None of the views in this letter represent any of the official positions of any of these regulatory bodies. Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited. References 1. de Vries F, de Vries C, Cooper C, Leufkens B, van Adenosine triphosphate Staa T-P (2006) Reanalysis of two studies with contrasting results on the association between statin use and fracture risk: the General Practice Research Database. Int J Epidemiol 35:1301–1308PubMedCrossRef 2. US Food and Drug Administration FDA (2010) Possible fracture risk with high dose, long-term use of proton pump inhibitors. http://​www.​fda.​gov/​Drugs/​DrugSafety/​PostmarketDrugSa​fetyInformationf​orPatientsandPro​viders/​ucm213206.​htm. Accessed 28 May 2010 3. Yang YX, Lewis JD, Epstein S, Metz DC (2006) Long-term proton pump inhibitor therapy and risk of hip fracture. JAMA 296:2947–2953PubMedCrossRef 4.

The survey takes approximately 10 minutes to complete and is written at the sixth-grade reading level. Practicing physicians consider the survey a feasible tool to assess patients’ dietary habits and it is valid against the Healthy Eating Index in medical students and against food frequency questionnaires in the general population [12]. Good test-retest reliability (r = 0.86) was reported in ethnically and educationally diverse groups [12]. In the current study, only nutrition questions were examined. Answers were coded according

to previous studies with usually/often = 1, sometimes = 2, rarely/never = 3, and blank answers = 3 [13]. Questions are phrased so higher scores indicate healthier eating behaviors. The alcohol use answers www.selleckchem.com/products/BIBW2992.html were categorized by frequency of alcohol BMS202 cost consumption over the past month. Frequency of consuming >1-2 drinks were categorized as 0–1 times = rarely/never(3), 1–6 times = sometimes(2), and >6 times = usually/often(1). Body weight (to the nearest 0.5 lbs.) and height (to the nearest 0.5 inch) were collected during the athlete’s pre-participation physical examination. Waist circumference was obtained by using a standard tailor’s

tape measuring the narrowest portion of the waist between the xyphoid process and naval, recorded to the nearest quarter inch and expressed in centimeters. Weight was measured on a laboratory scale. Data analysis PCA was conducted with the first wave of data using the scree plot to determine the number of components to retain. EFA was conducted on the second wave of data to represent the realistic nature of the study measurement. Proportion of common variance >0.75 and chi-square significance test of retained factors against the inclusion of an additional factor were criteria used to determine the number of factors to retain. The second wave of athletes was surveyed to avoid dependency among the data. Last, a Resminostat CFA, designed to test the fit of the exploratory factor model was performed. Factor score coefficients were obtained

from the confirmed model output and scores were computed for each participant on each dietary pattern. After progressing through the model identification steps to establish the construct validity of the REAP, male and female athletes were stratified by participation in aesthetic, or appearance-oriented sport; or non-aesthetic sport, in which success is not related to appearance. Aesthetic sports included gymnastics, swimming, diving, and wrestling. Non-aesthetic sports included golf, basketball, baseball, softball, soccer, football, volleyball, cross-country/track and field, water polo, and tennis. Mean differences between pattern scores were AG-881 purchase explored between aesthetic classification (aesthetic sport vs.

Proc Roy Soc Lond B 274(1608):303–313CrossRef Kuldna P, Peterson K, Poltimaee H, Luig J (2009) An application of DPSIR framework

to identify issues of pollinator loss. Ecol Econ 69:32–42CrossRef LeBuhn G, Droege S, Connor EF, Gemmill-Herren B, Potts SG, Minckley RL, Griswold T, Jean R, Kula E, Roubik DW, Cane J, Wright KW, Frankie G, Parker F (2013) Detecting insect pollinator declines on regional and global scales. Conserv Biol 27:1–13CrossRef Lonsdorf E, Kremen C, Ricketts T, Winfree R, Williams S, Greenleaf S (2009) Modelling pollination services across agricultural landscapes. Ann Bot 103:1589–1900PubMedCentralPubMedCrossRef GSK458 Lye G, Park K, Osborne J, Holland J, Goulson D (2009) Assessing the value of rural stewardship schemes for providing foraging resources and nesting habitat for bumblebee queens (Hymenoptera: Apidae). Biol Conserv 142:2023–2032CrossRef Natural England (2010) entry level stewardship, 3rd edition. http://​naturalengland.​etraderstores.​com/​NaturalEnglandSh​op/​NE226 Natural England (2012) New (O)ELS options available and option changes from 1st January 2013. http://​www.​naturalengland.​org.​uk/​Images/​new-ELS-options-info-note_​tcm6-32527.​pdf Natural England (2013a)

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England (2013c) Higher Level Stewardship, 4th Edition. http://​publications.​naturalengland.​org.​uk/​file/​2819648 Nix J (2010) Farm management pocketbook, 41st edn. The Andersons Centre, Melton ifenprodil Mowbery Ollerton J, Winfree R, Tarrant S (2011) How many flowering plants are pollinated by animals? Oikos 120(3):321–326CrossRef Potts SG, Woodcock BA, Roberts SPM, Tscheulin T, Pilgrim ES, Brown VK, Tallowin JR (2009) Enhancing pollinator biodiversity in intensive grasslands. J Appl Ecol 46(2):369–379CrossRef Potts SG, Roberts SPM, Dean R, Marris G, Brown MA, Jones R, Neumann P, Settele J (2010) Declines of managed honeybees and beekeepers in Europe. J Apic Res 49:15–22CrossRef Pywell RF, Meek WR, Loxton RG, Nowakowski M, Carvell C, Woodcock BA (2011) Ecological restoration on farmland can drive beneficial functional responses in plant and invertebrate communities. Agric Ecosyst EPZ-6438 in vivo Environ 140:62–67CrossRef Ricketts T, Lonsdorf E (2013) Mapping the margin: comparing marginal values of tropical forest remnants for pollination services. Ecol Appl 25:1113–1123 SAFFIE (2007) Cost:benefit analysis of the best practices for increased biodiversity, Chapter 8, HGCA. http://​www.​hgca.​com/​publications/​documents/​cropresearch/​PR416_​SAFFIE_​8_​Cost_​benefit_​analysis.

The bladder had to be taken at middle filling by voiding it 1.5 hours before simulation and daily before each treatment session. The acquired images were then transferred to the Eclipse (v.8.9) treatment planning system. The clinical target volume (CTV) consisted of the prostate and entire seminal vesicles,

the planning target volume (PTV) was obtained by adding 1 cm margin in all directions except toward the rectum, where the margin was reduced to 0.6 cm according to our institutional policy [19]. The rectal and bladder walls were contoured as critical normal structures, in particular, the rectum G418 solubility dmso was outlined from the sigmoid flexure to the anal margin. Patients were treated with a 15

MV five-field sliding window IMRT technique. The beam arrangement was: posterior (0°), right posterior oblique (75°), right anterior oblique (135°), left anterior oblique (225°) and left posterior oblique (285°). Plans were optimized to give at least 95% and 90% of the prescribed dose to CTV and PTV, respectively. The maximum dose heterogeneity within the PTV was set at 17% (from 90% to 107%). No constraints were applied to the overlapping volume between the PTV and rectum, which was treated as PTV. Dose-volume constraints were set for rectal and selleck chemicals bladder walls and ISRIB datasheet femoral heads. Dose-volume constraints were: maximum 70 Gy, 50 Gy and 40 Gy Interleukin-3 receptor to 30%, 50% and 60% of the rectal wall volume, respectively, maximum 70 Gy and 50 Gy to 50% and 70% of the bladder wall volume, respectively, and maximum 55 Gy to 70% of the femoral heads. The normal tissue planning limits were based on our prior experience and on previously published studies [20–25]. Dose-volume histograms were recorded for all patients. Patients were treated with Varian 2100 linear accelerators (Varian Associates, Palo Alto, CA) equipped with 120-leaf multi-leaf collimators. The accuracy of the set-up

was monitored daily by verifying the position of the isocenter comparing skeletal landmarks on orthogonal portal images acquired with an electronic portal imaging device (EPID) to the digitally reconstructed radiography (DRRs). Study endpoints The primary endpoint of our study was gastrointestinal (GI) and genitourinary (GU) toxicity. Early and late toxicity data were scored according to the Cancer Therapy Evaluation Program, Common Terminology Criteria for Adverse Events, Version 3.0 [26]. Grade 1–4: Grade 1 (mild) – asymptomatic or mild symptoms requiring only clinical or diagnostic observation; Grade 2 (moderate) – minimal, local or noninvasive intervention indicated; Grade 3 (severe) – severe or medically significant but not immediately life-threatening requiring hospitalization, prolonging hospitalization or affecting activities of daily living; Grade 4- life-threatening consequences requiring urgent intervention.

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of endocrine treatments by injection or tablets: results from a study of women with breast cancer. Ann Oncol ISRIB supplier 17:205–210PubMedCrossRef 13. Granger AL, Fehnel SE, Hogue SL, Bennett L, Edin HM (2006) An assessment of patient preference and adherence to treatment with Wellbutrin SR: a web-based survey. J Affect Disord 90:217–221PubMedCrossRef

14. Reginster JY, Rabenda V, Neuprez A (2006) Adherence, patient preference and dosing BAY 1895344 in vivo frequency: understanding the relationship. Bone 38:S2–S6PubMedCrossRef 15. Kostenuik PJ (2005) Osteoprotegerin and RANKL regulate bone resorption, density, geometry and strength. Curr Opin Pharmacol 5:618–625PubMedCrossRef 16. Bekker PJ, Holloway DL, Rasmussen AS et al (2004) A single-dose placebo-controlled CHIR-99021 molecular weight study of AMG 162, a fully human monoclonal antibody to RANKL, in postmenopausal women. J Bone Miner Res

19:1059–1066PubMedCrossRef 17. McClung MR, Lewiecki EM, Cohen SB et al (2006) PF-6463922 order denosumab in postmenopausal women with low bone mineral density. N Engl J Med 354:821–831PubMedCrossRef 18. Lewiecki EM, Miller PD, McClung MR et al (2007) Two-year treatment with denosumab (AMG 162) in a randomized phase 2 study of postmenopausal women with low BMD. J Bone Miner Res 22:1832–1841PubMedCrossRef 19. Brown JP, Prince RL, Deal C et al (2009) Comparison of the effect of denosumab and alendronate on BMD and biochemical markers of bone turnover in postmenopausal women with low bone mass: a randomized, blinded, phase 3 trial. J Bone Miner Res 24:153–161PubMedCrossRef 20. Cummings SR, San Martin J, McClung MR et al (2009) Denosumab for prevention of fractures in postmenopausal women with osteoporosis. N Engl J Med 361:756–765PubMedCrossRef 21. Kendler DL, McClung MR, Freemantle N et al (2011) Adherence, preference, and satisfaction of postmenopausal women taking denosumab or alendronate. Osteoporos Int 22:1725–1735 22. Horne R, Weinman J, Hankins M (1999) The beliefs about medicines questionnaire: the development and evaluation of a new method for assessing the cognitive representation of medication. Psychol Health 14:1–24CrossRef 23. Gold DT, Horne R, Hill C, Borenstein J, Varon S, Macarios D (2008) Development, reliability, and validity of a new preference satisfaction questionnaire (PSQ). J Bone Miner Res 23:S210–S211 24.

30) $$ \frac\rm d \varrho_x\rm d t = – 2 \mu \nu x + 2 \mu c + 2 \alpha c \sqrt\fracx\varrho_x2 , $$ (5.31)with similar equations for \(y,\varrho_y\). Transforming to total concentrations and relative chiralities by PI3K inhibitor way of $$ x = \displaystyle\frac12 z (1+\theta) , \quad y = \displaystyle\frac12 z (1-\theta) , \quad \varrho_x = \displaystyle\frac12 R (1+\zeta) , \quad \varrho_y = \displaystyle\frac12 R (1-\zeta) , $$ (5.32)we find $$ \frac\rm d c\rm d t = \mu \nu z – 2 \mu c – \frac\alpha c \sqrtz R2\sqrt2 \left[ \sqrt(1+\theta)(1+\zeta) + \sqrt(1-\theta)(1-\zeta)

\right] , \\ $$ (5.33) $$ \beginarrayrll \frac\rm d z\rm d t & = & 2\mu c – \mu \nu z – \alpha c z

– \frac12 \xi z^2 (1+\theta^2) \\ && + \frac\beta \sqrtzR2\sqrt2 \left[ \sqrt(1+\theta)(1+\zeta) + \sqrt(1-\theta)(1-\zeta) \right] \\ && – \frac\xi z^3/2 R^1/24\sqrt2 SRT1720 \left[ (1+\theta)^3/2 (1+\zeta)^1/2 + (1-\theta)^3/2 (1-\zeta)^1/2 \right] \\ && – \frac\beta z^3/2 \sqrt2R \left[ \frac(1+\theta)^3/2(1+\zeta)^1/2 + \frac(1-\theta)^3/2(1-\zeta)^1/2 \right] , \\ \endarray $$ (5.34) $$ \frac\rm d R\rm d t = – 2\mu\nu z + 4 \mu c + \frac12 \alpha c \sqrt2zR \left[ \sqrt(1+\theta)(1+\zeta) + \sqrt(1-\theta)(1-\zeta) \right] , \\ $$ (5.35)together with the Eqs. 5.38 and 5.39 for the relative chiralities θ and ζ, which will be analysed later. Since the equations for d R/ddt and dc/dt are essentially the same, we obtain a third piece of information from the requirement that the total mass in the system is unchanged from the initial data, hence the new middle equation above. Solving these we find \(c=\frac12 (\varrho-R)\) and use this in place of the equation for c. In the symmetric case (θ = ζ = 0) we obtain the steady-state conditions $$ 0 = 2\mu\nu z – 4\mu c – \alpha c \sqrt2zR filipin , \qquad\qquad \varrho \; = \; R + 2 c , \\ $$ (5.36) $$ 0 = 2\mu c – \mu \nu z – \alpha c z – \frac12 \xi z^2 + \frac12 \beta \sqrt2zR

– \beta z \sqrt\frac2zR – \frac\xi z2 \sqrt\fraczR2 . $$ (5.37)For small θ, ζ, the equations for the chiralities can be approximated by $$ \beginarrayrll \frac\rm d \theta\rm d t & = & – \left( \frac2\mu cz + \frac12 \xi z + \frac12 \beta \sqrt\Volasertib molecular weight fracR2z + \frac12 \beta \sqrt\frac2zR + \frac14 \xi \sqrt\fraczR2 \right) \theta \\ && + \left( \frac\beta(R+2z)2\sqrt2zR – \frac\xi4 \sqrt\fracRz2 \right) \zeta , \\ \endarray $$ (5.38) $$ \frac\rm d \zeta\rm d t = \left( \frac2\mu\nu zR – \alpha c \sqrt\fraczR2 \right) \theta – \left( \frac2\mu\nu zR – \frac4\mu cR \right) \zeta , $$ (5.