zilongwang/ReadingBank huggingface dataset:
DISCUSS 2. Nurses perform their role as a motivator, advocate, and educator appropriate to the circumstances. Description of Motivator: The presence of nurses in addition to help medical healing action, is also to motivate the clients to be willing to undergo treatment in accordance with the procedures. Discussion is to provide motivation for the patient to follow medical procedures, to maintain a healthy lifestyle, etc. (Motivational conversation) Description of Advocator: Nurses serve as advocates associated with the problems of family involvement in decision making to use traditional medicine, nutrition, treatment and clinical decisions. Nurses are advised to discuss the matter to the experts, so the nurses may ask cooperation of the physicians, nutritionists and pharmacists or others to provide information to the client. Description of Educator: role provides relevant information to the client about the client's ignorance of the disease, nurse activity here is as a health educator. 3. Summing up and evaluating the results of the conversation with the patient. Description: Evaluating subjectively by asking for results of the patient's actions based on the patient’s perspective and evaluating objectively the patients' knowledge on the actions that have been taken or obtained based on observation during current actions A nurse as a motivator: When is a client that is not routine in having chemotherapy, the nurse as a motivator, "Ma’am, you should be in a routine for chemotherapy series to recover from you illness. Or do you have any further requirenment about this chemotherapy? Answer from the client may be further discussed with the doctor. A nurse as an advocator: When doctors give drugs eg antibiotics, nurses can communicate with the doctor what medications that their client is not suitable, for example because of allergies. "Ma’am, I will later discuss with the doctor about the appropriate antibiotics for you. He may change the substance. Please do not worry. " A nurse as an educator: For example when the client is allowed to go home, nurses as educator povide information of the procedure, "Sir, later at home, this is how to treat the injury......... (Describing way and procedure)." Examples of evaluating results of conversation: Subjective evaluation: "How it feels after installed Catheter?" Objective Evaluation: "Do you already know how the catheter works later?" Structure The contents of Communication Skills oriented on Nursing Care Strengthening of Nurse-Client Communication Skills
How many days are you staying in Nepal during this visit including your stay in Chitwan National Park? _____________days Section B: Your ecotourism experience How would you rank the following statement (a to f) on a scale of 1 to 5? A ‘1’ indicates ‘strongly disagree’ and ‘5’ indicates ‘strongly agree’. [Please circle one response only for each question] There are too many people visiting the park. The park is overcrowded. Strongly Strongly Disagree Agree 1 2 3 4 5 Recreational activities (elephant riding, jungle canoeing, etc) in and around the park cause disturbances to park wildlife. Strongly Strongly Disagree Agree 1 2 3 4 5 The park administration has taken adequate measures to conserve its iconic species – one horned Rhino, royal Bengal tiger. Strongly Strongly Disagree Agree 1 2 3 4 5 I am concerned about solid waste (litters) pollution in and around the park. Strongly Strongly Disagree Agree 1 2 3 4 5 I am concerned about water pollution (in rivers and lakes) in and around the park. Strongly Strongly Disagree Agree 1 2 3 4 5 The hotels and restaurants in and around the park have adequate facilities to meet visitors’ needs. Strongly Strongly Disagree Agree
23. I plan to travel again to experience overseas cannabis tourism. 1 2 3 4 5 6 7 24. I travel again to experience overseas cannabis tourism. 1 2 3 4 5 6 7 25. I am eager to travel again to experience overseas cannabis tourism. 1 2 3 4 5 6 7 26. I will recommend experiencing overseas cannabis tourism to my friends. 1 2 3 4 5 6 7 Demographic Information: 27. Age: ☐ 18-25 ☐ 26-35 ☐ 36 and above 28. Educational background: ☐Secondary ☐School/vocational school ☐College/university ☐Postgraduate 29. Annual income in RMB (1 RMB ≈ 0.16 USD): ☐ 100,000 or ☐ 100,001 – 200,000 ☐ 200,001 – 300,000 ☐ 300,001 – 500,000 30. Marital status: ☐ Single ☐ Married 31. Travel types in Amsterdam for the purpose of commercial cannabis: ☐ Alone ☐ Small group with friends ☐ group with strangers ☐ Big group with friends ☐ Big group with strangers 32. Information sources on travelling to Amsterdam on the purpose of commercial cannabis: ☐Internet search ☐Relevant Internet forum ☐Friends' word of mouth ☐Advertisement ☐Others 33. Gender: ☐ Male ☐ Female 34. Did you smoke cannabis before: ☐ Yes ☐ No Filter Questions: 35. Cannabis smoking is one of my major leisure activities during this trip. ☐ Yes ☐ No 36. Cannabis smoking is one important part of this travelling experience.
drop heavy particle, 6 – Incoming woody is de-moisturized by hot syngas, 7 – Condensable gases containing syngas are cooled down to trap tars, 8 – Filter housing collects fly ash fine dust, 9 – Cleaned syngas is fed into either burning in an IC engine or compressing in a holder tank (No.10) and flaring (No.11), respectively Fig. B2 Photograph of genset intakes syngas as fueled in a spark ignition internal combustion engine, as following: 12 – Air mixer control box, 13 – an inline 4 cylinder engine, 14 – Turbocharger, 15 – Exhaust gas line, 16 – Intercooler and cooling unit and 17 – Electric generator Fig. B3 The compressed and stored syngas system from gasification process Syngas storage system
The syngas-to-power can be synchronized seamlessly to hybrid solar PV/battery system for backup electric generation. The deficient power generated by solar PV arrays can then be complemented at sudden time when the battery level drops while discharging. One day before switching to syngas genset, the cleaned syngas effluent was prepared in a gas storage tank (as shown in Fig. B3) which was typically located separately to the main gasifier unit. The gas storage tank acts as a buffer in order to balance fluctuations in the production of gas in the gasification process. Afterward the syngas was let to flow into the receiver of gas holder, which from here was ready to be compressed into the syngas container until reach approximately 10 bar gauge. The storage capacity of the syngas network is more than 140 kW which is large enough to supply for one week at a standby condition. When syngas production levels are highly variable, dual fuel mixing can be used to supplement the syngas with liquefied petroleum gas (LPG). At the beginning, when SOC dropped below 40%, the syngas genset was automatically started to be warming up at about 5 min of continuous idle operation (900 rpm). The air-fuel mixture under lean-burn conditions was adjusted by a control box until the genset run stably. According to Fig. B4, the solenoid operated butterfly valve (CV-01) that will open by programming mechanism was installed to arrange the flow of the syngas. Together with syngas, the fresh air was flowed through CV-02 into the mixer, and directed in to the electronic hydraulic actuator of the combustion chamber. It should be noted here that during starting the genset, the flow rate of the syngas was let maximum and reduce the rate until the genset start running. After that, the genset was accelerated at the synchronous speed of 1500 rpm (frequency 50 Hz and voltage range 380-415 V). Once the SOC was reached its target point, the genset automatically shuts. Fig. B4 A schematic diagram of the air/fuel intake manifold with the syngas engine through the speed governor system
Supplementary 1. ICD9 codes used to identify underlying medical conditions ICD9 Code ICD9 condition name Cardiac Disease 093 112.81 130.3 391 392 393-398 402 404 410-414 415 416 417 421 423 424 425 427 428 429 440 442 443 Cardiovascular syphilis Candidal endocarditis Myocarditis due to toxoplasmosis Rheumatic fever with heart involvement Rheumatic chorea Chronic rheumatic heart disease Hypertensive heart disease Hypertensive heart and chronic kidney disease Ischemic heart disease Acute pulmonary heart disease Chronic pulmonary heart disease Other diseases of pulmonary circulation Acute and subacute endocarditis Other diseases of pericardium Other diseases of endocardium Cardiomyopathy Cardiac dysrhythmias Failure Ill-defined descriptions and complications of disease Atherosclerosis Other aneurysm Other peripheral vascular disease
403 Hypertensive renal disease Hemoglobinopathies HIV/AIDS 042 043 044 V08 Human immunodeficiency disease Human immunodeficiency disease Human immunodeficiency disease Asymptomatic human immunodeficiency virus infection status Immunosuppression
335 340 341 343 344.0 345 348 356 358 359.1 359.2 438 741 742 756.4 780.3 783.42 Multiple sclerosis demyelinating diseases Infantile cerebral palsy Quadriplegia and quadriparesis Epilepsy and recurrent seizures conditions of the brain Hereditary and idiopathic peripheral neuropathy Myasthenia gravis Hereditary progressive muscular dystrophy Myotonic disorders Dementia and stroke bifida Other congenital anomalies of the nervous system Chondrodystrophy Convulsions Delayed milestones Cerebrovascular disease Pregnancy complications 640-648 767 Complications related to pregnancy Birth trauma
Gender, age group, family social class, education, chronic diseases, self-reported health, GP visit in last 30 days Skilled and unskilled working class 1.21 (1.11–1.33) Self-employed persons 1.18 (1.07–1.31) White collar and small employers 1.01 (0.92–1.12) Managers, professionals and entrepreneurs. 1 Christenson[] 2002 Education Relationship status SIV & PV SIV Unadjusted Education (4) Elementary school 1 (Raw data) Junior secondary school 1.37 (1.20-1.56) Upper secondary school 1.44 (1.23-1.67) University/college 1.67 (1.45-1.92) Relationship status (2) Married/living with partner 1 (Raw data) Widowed/living alone 0.76 (0.69-0.84) PV Education (4) Elementary school 1 (Raw Data) Junior secondary school 1.32 (1.17-1.50) Upper secondary school 1.38 (1.19-1.59) University/college 1.44 (1.26-1.63) Relationship status (2) Married/living with partner 1 (Raw data) Widowed/living alone 0.73 (0.66-0.80) Crawford[] 2011 Living arrangements Relationship status Location: residence Social class SIV Living arrangements (2) Adjusted for gender, age, marital status, living status, social class, home location, geographical location Lives with others 1.14 (0.83-1.67)* (AOR) Lives alone 1 Location: residence (2) Urban 1.15 (0.91-1.43)* (AOR) Rural 1 Relationship status (3) Married 1 (AOR) Single 1.3 (0.8–2.1) Widowed 1.5 (1.1–2.3) Social class (2) Higher 1 (AOR) Lower 0.95 (0.7–1.2) Damiani[] 2007 Education Income/ wealth Relationship status Social class SIV Education (4) University degree 1.05 (0.87-1.28)* AOR Upper secondary education -
Studies also included in the review Bodekar[] Germany Seasonal influenza March-June 2014 825 Respondents aged ≥60 years from a nationwide telephone survey Immigration status was not associated with SIV uptake Sarria-Santamera[] Spain Seasonal influenza 1997 1148 Non-institutionalised participants (aged ≥65 years) to the Spanish National Health survey (ENS) No differences were found by availability of private health insurance or marital status on vaccine uptake
Table S7. Consequences of arteriovenous fistula on the cardiovascular system Immediate Days-weeks Weeks-months Decrease in blood pressure Increase in blood volume Further increase in cardiac output Reduced arterial stiffness Increase in LV end diastolic volume Increase in LV mass and LV size Decrease in peripheral resistance Increase in atrial chamber size Increase in heart rate and stroke volume Diastolic and systolic dysfunction Increase in cardiac output Increase in pulmonary flows and later pulmonary hypertension LV, left ventricular. Reproduced from Rao et al.S22
($AU) QALYs Costs saved ($AU) QALYs saved Costs saved ($AU) saved Hospitalisations Meningitis 1,532,632 4.33 114,160 0.21 83,283 0.15 Bacteraemia 3,1998,752 21.69 271,062 0.77 174,641 0.62 IPD pneumoniaa 6,610,066 49.21 360,757 1.27 254,023 0.90 CAPb 386,596,351 6,760.26 1,318,177 10.57 0 0 GPc visits CAPb 10,192,120 671.76 49,979 1.73 0 0 Deaths Meningitis 0 57.65 0 3.32 0 2.54 Bacteraemia 0 220.61 0 8.44 0 6.52 IPD pneumoniaa 0 534.38 0 14.53 0 10 CAPb 0 59,847.96 0 62.00 0 0 408,129,921 68,167.85 2,060,135 102.84 511,947 20.73 a Invasive pneumococcal disease with clinical symptoms of pneumonia b Community-acquired pneumonia c General practitioner
X76EC Fever defervescence X76EE Central Xa3DL High temperature Xa9sd Low grade pyrexia Xaa6X H/Oe: fever XaB1J Recurrent febrile convulsion XaBf3 Pyrexia postprocedure XaIO1 Cough with fever H/O: febrile convulsions XaNSo Green traffic light - low risk of serious illness (Feverish illness in children 2007) XaNVy traffic light - intermediate risk of serious illness (Feverish illness in children 2007) XaNVz Red traffic light - high risk of serious illness (Feverish illness in children 2007) XE1gR [D]Fever NEC XE1iC Examination of fever XE1je Febrile convulsion (& O/E) O/E - hyperpyrexia (& > 40.5 o CEL) XM03l Febrile convulsion XM05S Pyrexia of unknown origin XM05T Acute rise of fever XM05U Gradual rise of fever XM05V Continuous XM05W Remittent fever XM05X Intermittent fever Staircase fever XM05Z Irregular fever XM09q O/E - fever XM0yv Pyrexia [D] XM0yw Hyperpyrexia [D] XM11j O/E - hyperpyrexia a On examination b Nothing abnormal detected c Not otherwise specified d Diagnostic code e History of
SA2 Not immunised n(%) Population Not fully immunised n(%) Population Not fully immunised n(%) Population Not fully immunised n(%) Population Maitland - North 20 (25.3) 79 7 (8.0) 88 1 (0.9) 117 28 (9.9) 284 Maitland 27 (30.7) 88 9 (9.8) 92 4 (4.9) 81 40 (15.3) 261 Maitland - East 121 (30.0) 403 24 (5.6) 432 30 (7.7) 389 175 (14.3) 1224 Maitland - West 132 (38.9) 339 36 (10.7) 337 10 (3.0) 333 178 (17.6) 1009 Total 300 (33.0) 909 76 (8.0) 949 45 (4.9) 920 421 (15.2) 2778 2016 One year Two year Five year Total SA2 Not fully immunised n(%) Population Not fully immunised n(%) Population Not fully immunised n(%) Population Not immunised n(%) Population Maitland - North 17 (21.5) 79 1 (1.1) 88 4 (3.4) 117 22 (7.7) 284 Maitland 46 (52.2) 88 6 (6.5) 92 4 (4.9) 81 56 (21.4) 261 Maitland - East 131 (32.5) 403 20 (4.6) 432 12 (3.1) 389 163 (13.3) 1224 Maitland - West 150 (44.2) 339 24 (7.1) 337 12 (3.6) 333 186 (18.4) 1009 Total 344 (37.8) 909 51 (5.4) 949 32 (3.5) 920 427 (15.4) 2778
Appendix A: Spot Prices and Futures Prices and Sources (in Parentheses) Regions Crude Oil Spot Prices Crude Oil Futures Prices Natural Gas Spot Prices Natural Gas Futures Prices United States WTI (West Texas Oklahoma (EIA) WTI Crude Oil (EIA/NYMEX)* Henry Hub (Bloomberg) NYMEX Natural Gas Future (EIA/NYMEX) Canada N.A. N.A. AECO C Hub Natural Gas (Alberta, Canada) NYMEX Natural Gas Future (EIA/NYMEX) Latin America WTI (West Texas Oklahoma (EIA) WTI Crude Oil (EIA/NYMEX)* N.A. N.A. Middle East Arabian Gulf Dubai Fateh Crude Oil (Bloomberg) WTI Crude Oil (EIA/NYMEX)* N.A. N.A. United Kingdom Brent-Europe (EIA) Brent Crude Oil (Bloomberg) British Virtual Gas Hub Natural Gas ICE (UK) National Balancing Point Natural Gas Future (ICE) OPEC Arabian Gulf Dubai Fateh Crude Oil (Bloomberg) WTI Crude Oil (EIA/NYMEX)* N.A. N.A. *In companion analyses, we estimate our primary model explaining changes in oil rig count using Brent Crude Oil futures prices (sourced from Bloomberg).
Advisory work (direct contact with farmers) Research and development Administration and management Others (please specify) 11 Methods of advisory work. Please give a percentage estimate of the dominant working methods used by your advisory (Each answer must be between 0 and 100. The sum must be at most 100) Individual extension (one to one advice on the farm or over the telephone) Group extension (small group advice on/off the farm) Mass extension (internet, website tools, publications, radio, TV) 12 Clients number of farms covered by your advisory services (your client base)? Average number of farms served by one of your advisors annually? Average size (ha) of the farms covered by your advisory services? 13 Please indicate the main client groups targeted for advisory services by your organisation: Major target group Minor target group Not targeted by advisory services Large commercial farms (gross margin >£41,000 / >48000€)* Medium commercial farms (gross margin <£41,000 / >48000€ and >£16,000 / >19200€)* Small commercial farms (gross margin <£16,000 / >19200€)* Semi-subsistence farms (producing slightly beyond own needs, approx. 1-5 ha)* Subsistence farms (producing mainly for own needs (< 1ha)* Agricultural producer groups Young farmers Female farmers Part-time farmers Farm-employees Other (please specify) *definitions according to European Size Units (ESU) stated on ec.europa.eu/eurostat 14 (please specify) 15 Did the advisors in your organisation receive any training in 2012?
Table A2 – Contaminant sources and types contributing with nitrogen and phosphorus to stream water in the Umia River basin. Literature references: (a) Ryding and Rast (1992); (b) Directiva 200/660/CE (2008); (c) and (d) Reports of Galicia municipalities (BNAE, 2008). The yields relative to contaminant source “Agriculture” and type “Other” are the mean values of all other contaminant types of the same source. Contaminant source Contaminant type Nitrogen yield Phosphorus yield Literature reference (yield unit) Domestic sewage (a) (kg.capita–1.y–1) Human activities 4.75 0.73 Livestock production Leachates from animal excreta (b) (kg.head–1.y–1) Cattle 65.11 32.91 Sheep 6.47 0.96 Goat 8.71 1.29 Pig 9.37 2.7 28.02 30.02 Poultry 0.69 0.21 Agriculture Leachates from farmland fertilizers (c) (kg.ha–1.y–1) Cereal 9.02 25.51 Fodder 62.60 92.90 Pataca 63.36 32.26 Leguminous 5.33 -6.67 Horticultural 49.87 12.26 Fruit tree –48.28 –55.11 Chestnut tree 0.00 0.00 Vineyard –16.86 –72.40 Grazing 33.98 43.58 Other 17.7 8.0 Runoff from areas with < 10% occupation by agriculture plus urban area (d) (kg.ha–1.y–1)
Comment: This clause is becoming more common but fails to disclose the actual legal position as to the consumer guarantees – as such it may be argued to be misleading to a consumer under ACL section 64. COMMITMENTS ABOUT THE CONTENT WITHIN THE SERVICES, THE SPECIFIC FUNCTIONS OF THE SERVICES, OR THEIR RELIABILITY, AVAILABILITY, OR ABILITY TO MEET YOUR NEEDS. WE PROVIDE THE SERVICES “AS IS”. SOME JURISDICTIONS PROVIDE FOR CERTAIN WARRANTIES, LIKE THE IMPLIED WARRANTY OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NON-INFRINGEMENT. TO THE EXTENT PERMITTED BY LAW, WE EXCLUDE ALL WARRANTIES. Comment: This clause fails to disclose the actual legal position as to the consumer guarantees (it does not expressly exclude them via its reference to ‘warranties’ nor exoressly preserve them via use of the phrase ‘to the extent permitted’) – as such it may be argued to be misleading to a consumer under ACL section 64. Canonical cannot be held liable for any direct or indirect damage or loss caused by connection speed. Canonical will use reasonable efforts to ensure availability of the services, but makes no guarantee that the services will be available without interruption. Canonical is not responsible for the loss of any of your data or any loss of business or financial disadvantage to you as a result of any loss of or damage to your data as consequence of your use of the services. Comment: This clause fails to disclose the actual legal position as to the consumer guarantees – as such it may be argued to be misleading to a consumer under ACL section 64. Term which purports to bind consumer even where contract, consumer or other law may indicate otherwise. YOU ACKNOWLEDGE THAT YOUR ELECTRONIC SUBMISSIONS CONSTITUTE YOUR AGREEMENT AND INTENT TO BE BOUND BY AND TO PAY FOR SUCH AGREEMENTS AND TRANSACTIONS. YOUR AGREEMENT AND INTENT TO BE BOUND BY ELECTRONIC SUBMISSIONS APPLIES TO ALL RECORDS RELATING TO ALL TRANSACTIONS YOU ENTER INTO ON THIS SERVICE, INCLUDING NOTICES OF CANCELLATION, You must be at least 13 years old to use our services. If you are between age 13 and 18, you confirm that you have your parent's or legal guardian's consent to use the services and that they have read and agreed to this agreement. Conclusion: this consent is problematic it relies upon undertakings from minors. Changes to the services or this agreement: we may occasionally change
Fusarium venenatum IBT 1338 Memnoniella echinata IBT 9789 Memnoniella echinata IBT 9791 Stemphylium versicarium IBT BA910 Ulocladium atrum IBT BA1539 Ulocladium cucurbitae IBT BA1540 Ulocladium cucurbitae IBT BA520
Supplementary 2. Types of Microplastics Identified with Micro-FT-IR for the Particles Randomly Selected from mussles. composition of particles numbera Percentage (%) particles measured 129 100 plastic particles 109 84.5b Cellophane (CP) 53 41.1c Polyethylene teraphalate (PET) 21 16.3 Polyester, terephthalic acid 14 10.9 Polymerized,oxidized material (POM) 9 7.0 Polyethylene (PE) 4 3.1 Poly(N-methyl acrylamide) 3 2.3 Silk II 2 1.6 Poly(oxymethylene:oxyethylene) 1 0.8 Poly(acrylonitrile:acrylic acid) 1 0.8 Poly(1-dodecene) (PC12) 1 0.8 nonplastic particles 11 8.5 unidentified particles 9 7.0 a Number of particles. b The percentage of plastic particles in all the measured particles from mussles. c The percentage of each type in all the plastic particles from mussles.
described in Ran et al. (2002). In brief, about 5 g of the frozen-dried sediment sample was treated with 10% HCl for 24 h to remove inorganic carbon, and then dried overnight at 105°C. The organic carbon contents were determined on an elemental analyzer (Vario EL III Elementar, Germany) with acetanilide used as external standard. Sample duplicates were processed and their mean values are reported in Table 1. E.coli and total coliform groups in seawater samples were measured using the membrane filtration method adopted by the Environmental Protection Department, the Government of the Hong Kong Special Administrative Region (). Sample extraction, clean-up, and analysis：Phenolic estrogens Phenolic estrogens in seawater, sediment and biota samples (Gatidou et al., 2010; Zhao et al., 2011) One litre of each of the seawater samples was filtered through a glass fibre filter (Whatman GF/F, 0.7 μm, UK). Methanol was used to elute non-filterable particles on the filter and combined with the filtered sample. For solid phase extraction (SPE), 100 μL each of 1 mg/L of 4-n-NP was added to each sample as an internal standard. SPE cartridge (Oasis HLB, 6 mL, 500 mg) was preconditioned with methanol / HPLC water (1:1, v/v). The filtered water samples passed through the SPE cartridges at 10 mL/min. The target compounds were eluted from the cartridges using methanol and dichloromethane. The extracts were dried and then re-dissolved in methanol. Target compounds in the sediment or tissue samples were extracted by ultrasonic-assisted solvent extraction. Five grams of the prepared samples were mixed with ethyl acetate (10 mL). The tube was ultrasonicated for 15 min and centrifuged at 1370 g for 10 min, and the supernatant was collected. The sediments were extracted two more times with 10 mL and 5 mL of ethyl acetate, respectively. The supernatants were combined and concentrated to about 1 mL on a rotary
7 MF 10.7 Pmin 149 38 12.6 19.9 7.9 1 4.0 8 MF 23.8 Pnom 336 103 10.0 17.9 3.5 2 4.1 9 L1 9.0 Pmin 130 35 11.7 20.1 10.7 1 5.1 10 L1 18.8 Pnom 293 94 11.7 18.7 4.0 1 4.2 11 WW 9.0 Pmin 127 38 12.7 19.9 7.7 2 5.2 12 WW 14.1 Pnom 231 95 15.6 19.0 2.7 2 3.6 Boiler with down-draught combustion (B3) 13 DW 7.5 Pmin 161 69 11.7 20.3 14.4 1 4.6 14 DW 15.2 Pnom 208 75 14.6 19.1 3.5 1 4.4 15 MF 8.4 Pmin 205 36 9.6 20.3 15.7 1 3.9 16 MF 19.8 Pnom 238 56 10.4 19.3 6.3 1 2.9 17 L1 7.3 Pmin 176 34 10.3 20.2 12.9 1 4.4 18 L1 22.8 Pnom 248 82 11.0 17.9 3.2 1 5.7 19 WW 11.4 Pmin 180 63 15.6 19.5 3.5 1 2.5 Gasification boiler (B4) 20 MF 11.2 Pmin 143 37 11.4 19.9 8.9 1 4.5 21 MF 27.5 Pnom 279 73 7.9 17.5 3.8 1 4.1 22 L1 12.8 Pmin 139 34 9.8 19.6 8.1 1 6.8 23 L1 25.8 Pnom 264 74 9.2 18.1 4.0 1 3.9 Gasification boiler (B5) 24 WW 9.5 Pmin 114 38 14.8 20.0 6.3 1 4.0
Table S1. Primers used for quantification of RNA expressions by qPCR Gene Primer Sequence (5´-3´) Amplicon length (bp) Accession number PCR efficiency (%) eef1a1 F GTGGTAATGTGGCTGGAGAC R TGTGAGCAGTGTGGCAATC 138 AY422992.1 112.07 cyp1a F GCATTACGATACGTTCGATAAGGAC R GCTCCGAATAGGTCATTGACGAT 147 ENSDART00000038200 117.11 cyp1b1 F TGGATCATCCTGCTACTTGTCA R TCCACTACCCTGTCCACGTC 74 ENSDART00000099870.2 95.48 cyp1c1 F AGTGGCACAGTCTACTTTGAGAG R TCGTCCATCAGCACTCAG 130 ENSDART00000019953 114.36 cyp1c2 F GTGGTGGAGCACAGACTAAG R TTCAGTATGAGCCTCAGTCAAAC 116 NW_001877817.3 112.20
6:2 FTS ND 0.030 0.10 Compound Mean (ng L-1) MDLs (ng L-1) MQLs (ng L-1) FOSA ND 0.030 0.10 MeFOSA ND 0.030 0.10 MeFOSE ND 0.030 0.10 EtFOSE ND 0.030 0.10 MeFOSAA ND 0.030 0.10 EtFOSAA ND 0.030 0.10 a ND = not detected. Table S6. Average recoveries (%) of internal standards ± standard deviation (SD) for the field aqueous phase samples)for rivers and seas (n = 56) Internal standard Recovery ± SD [13C4]-PFBA 111 ± 29 % 87 ± 21 % [13C4]-PFOA 102 ± 23 % [13C9]-PFNA 102 ± 24 % 100 ± 24 % 97 ± 24 % 85 ± 23 % [18O2]-PFHxS 91 ± 25 % [13C4]-PFOS 102 ± 23 % [13C8]-FOSA 90 ± 21 % [d7]-MeFOSE 61 ± 21 % [d9]-EtFOSE 56 ± 20 % [d3]-MeFOSAA 107 ± 31 % [d5]-EtFOSAA 102 ± 30 % S7. Standard deviation (%) of duplicate river samples (n = 5) (ID R4, R7, R15, R17 and R23) SD (%) Average SD (%) for all PFASs PFBA PFOA PFNA PFDA PFUnDA PFDoDA FOSA PFOS Average SD (%) for PFAS 11 16 30 49 38 44 42 56 36
R25 Emån 34a 55 R26 Alsterån 11a 0.98 R27 Ljungbyån 4.1a 0.72 Baltic Proper R28 Lyckebyån 6.0a 1.1 R29 Mörrumsån 31a 6.2 R30 Helge Å 42a 36 R31 Kävlingeån 11a 3.0 Kattegat R32 Rönneån 11a 4.8 R33 Lagan 81a 11 R34 Nissan 47a 12 R35 57a 5.6 R36 Viskan 43a 9.9 R37 Göta älv [Alelyckan] 554a 82 R38 Nordre älv 355a 38 R39 Örekilsälven 24a 2.9 R40 Enningdalsälven 12a 1.5 a data from Swedish meteorological institute (SMHI)2 S14. Explained nariation (R2X and R2Y) from SIMCA® (Umetrics AB) modeling for PFASs and water chemistry, demographic, geographic and hydrological factors in Swedish rivers Factor Number of components R2X (cumulative) R2Y (cumulative) Catchment size 5 0.90 0.18
DOC 5 0.91 0.49 Flow 5 0.91 0.32 Latitude 5 0.92 0.72 Population density 5 0.92 0.67 Run-off 5 0.91 0.21 Total population 5 0.92 0.38 Water temperature 5 0.93 0.46 Latitude & population density 5 0.92 0.69 S15. Explained variation (R2X and R2Y) from by SIMCA® (Umetrics AB) modeling for PFASs and water chemistry, geographic and hydrological factors in the Baltic Sea and the Kattegat Factor Number of components R2X (cumulative) R2Y (cumulative) DOC 5 0.98 0.75 Latitude 4 0.98 0.85 Salinity 5 0.98 0.93 Water temperature 5 0.98 0.67
Bootstrapping (BS) mapping 100% 100% Mixed industry/agriculture (91%) (100 bootstrap runs, r2 = 0.8) Bootstrapping with displacement (BS-DISP) % of accepted # of in best fit # of swaps in DISP 100% 0 0 95% 0 5 37% 36 27 Computer run-time (hours) >15 >15 >15 Table S10. Seasonal average contributions (in percent) of each identified source to measured PM2.5 for 2009–2015. Study period Winter Spring Summer Fall Factor 1 Mixed industry/agriculture 39% 30% 38% 45% 45% Factor 2 O3-rich (biogenic) 26% 18% 39% 33% 20% Factor 3 Traffic 19% 32% 14% 9% 22% Factor 4 Biomass burning 11% 12% 7% 12% 8% Factor 5 urban 4.4% 8.2% 1.9% 1.7% 4.9%
Table S11. Correlation (r = Pearson correlation coefficient) of PMF-derived sources with other pollutants and meteorological parameters measured at Red Deer Riverside station for 2009–2015. PM2.5 NO NO2 NOX O3 SO2 H2S CO THC CH4 NMHC Wind speed Temperature Relative humidity industry/agriculture –0.18* –0.18* –0.47* –0.39* –0.05* –0.11* 0.07* –0.21* –0.24* –0.10* –0.41* 0.004 0.24* 0.11* O3-rich –0.18* –0.55* –0.57* –0.59* 0.90* –0.11* –0.28* –0.37* –0.41* –0.37* –0.33* 0.11* 0.34* –0.46* Traffic 0.39* 0.68* 0.97* 0.85* –0.58* 0.25* 0.16* 0.70* 0.47* 0.48* 0.29* –0.09* –0.63* 0.22* Biomass burning 0.29* 0.47* 0.43* 0.47* –0.36* 0.01 0.24* 0.34* 0.75* 0.47* 0.98* –0.14* –0.10* 0.16* Mixed urban 0.40* 1.0* 0.81* 0.94* –0.57* 0.22* 0.44* 0.70* 0.58* 0.52* 0.47* –0.10* –0.43 0.25* *Correlation is significant at p = 0.01
13 Spiramycin 8025-81-8 -- C43H74N2O14 14 Nitrofurans Furazolidone 67-45-8 C8H7N3O5 15 Quinolones Ciprofloxacin 85721-33-1 acid C17H18FN3O3 16 Difloxacin 98106-17-3 acid C21H19F2N3O3 17 Enrofloxacin 80214-83-1 C16H18N2O4S 18 Fleroxacin Fleroxacin acid C17H18F3N3O3 19 Flumequine acid C14H12FNO3 20 Lomefloxacin acid C17H19F2N3O3 21 Norfloxacin 70458-96-7 acid C16H18FN3O3 22 Ofloxacin 82419-36-1 (+/-)-9-Fluoro-2, acid C18H20FN3O4 23 Oxolinic acid 14698-29-4 acid C13H11NO5 24 Sarafloxacin 98105-99-8 acid C20H17F2N3O3 25 Sulfonamides Sulfadiazine 68-35-9 C10H10N4O2S
26 Sulfadimethoxine 122-11-2 6-Sulfanilamido-2,4-dimethoxypyrimidine C12H14N4O4S 27 Sulfamerazine S 127-58-2 Monosodium C11H11N4NaO2S 28 Sulfamethazine 57-68-1 C12H14N4O2S 29 Sulfamethoxazole 723-46-6 sulfonamide C10H11N3O3S 30 Sulfamonomethoxine 1220-83-3 sulfonamide C11H12N4O3S 31 Sulfapyridine 144-83-2 4-amino-N-(2-pyridinyl)-benzene sulfonamide C11H11N3O2S 32 Sulfaquinoxaline 59-40-5 4-Amino-N-2-quinoxalinyl-benzene sulfonamide C14H12N4O2S 33 Sulfathiazole 72-14-0 4-Amino-N-2-thiazolyl-benzene sulfonamide C9H9N3O2S2 34 Sulfisoxazole 127-69-5 sulfonamide C11H13N3O3S 35 Tetracyclines Chlortetracycline 57-62-5 C22H23ClN2O8 36 Doxycycline 100929-47-3 hydrochloride C22H24N2O8 37 Oxytetracycline 79-57-2 C22H24N2O9 38 Others Flavomycin 11015-37-5 -- C69H107N4O35P 39 Narasin 55134-13-9 Salinomycin, 4-methyl-,(4S)-; deriv. C43H72O11 40 Salinomycin 53003-10-4 C42H70O11
Table S3: Method performance of UHPLC-MS/MS and GC-MS/MS analyses. Pesticide Linearity of calibration response (r2) (%) Nectarb Recovery (%) MDL (ng/g) MQL (ng/g) LC spike: 1 ng/g GC spike: 100 ng/g LC spike: 10 ng/g GC spike: 1 µg/g Mean RSD Mean RSD acetamiprid 0.9877 17 - - 0.08 - 0.42 0.28 - 1.4 114 17 110 19 -cypermethrin 0.9951 1 - - 43 - 215 143 - 717 104 10 91 20 boscalid 0.9965 17 - - 0.82 - 4.1 2.1 - 10 102 7 109 14 carbendazim 0.9817 -18 - - 2.4 - 12 12 - 59 93 13 78 9 carboxin 0.9875 -6 - - 0.10 - 0.50 0.33 - 1.7 124 1 122 18 chlorothalonil 0.9958 62a - - 152 - 760 461 - 2304 116 7 98 3 chlorpyrifos 0.9985 55 a - - 38 - 188 100 - 500 104 10 111 12 chlothianidin 0.9980 -13 - - 0.22 - 1.1 0.76 - 3.8 119 16 120 6 epoxiconazole 0.9959 -11 2.2 - 11 9.1 - 46 140 11 99 15 6 8 9 2 4 b Pollen 0 3 0 x 2
Supplementary Tables Table S1. Summary of vehicle specifications Vehicle ID Manufacturer year a Main application Emission standard Fuel type GVW b (kg) Fuel injection system device Engine size (L) Mileage traveled (km) Test time Test place #1 Toyota 2010 Taxi Euro 3 Diesel 1695 CR c DOC d 1.7 520850 2013 Macao #2 Volkswagen 2012 Taxi Euro 4 Diesel 1452 CR DOC 2.0 2013 Macao #3 Renault 2013 Taxi Euro 5 Diesel 2140 CR DOC 2.0 90332 2013 Macao #4 TOYOTA 2010 Taxi Euro 3 Gasoline 1805 GDI e TWC f 1.6 18405 2013 Macao #5 Mazda 1993 Private Cars Euro 1 Gasoline 1240 PFI g 1.3 124870 2013 Macao #6 Volkswagen 2003 Private Cars China 2 Gasoline 1475 PFI TWC 1.8 195663 2015 Beijing #7 TOYOTA 2007 Private Cars China 3 Gasoline 1550 PFI TWC 2.4 103369 2015 Beijing #8 Buick 2014 Private Cars China 6 Gasoline 1930 PFI TWC 2.4 46199 2015 Beijing Note: a The model year could be one year earlier than the actual year of production and registration; b Gross vehicle weight; c Common rail; d Diesel Oxidant Catalyst; e Gasoline Direct Injection; f Three way catalyst; g Port-Fuel Injection. Table S2. Diameter parameters of each ELPI+ size channel (Dekati, 2016) Channel (ELPI+) CH1 a CH2 a CH3 CH4 CH5 CH6 CH7 CH8 CH9 CH10 CH11 CH12 CH13 CH14 CH15 D50 b (nm) 6 17 30 60 108 170 260 400 650 1000 1600 2500 4400 6800 10000 Di c (nm) 10 22 42 80 140 210 320 510 800 1300 2000 3300 5500 8200 Note: a Newly added size channels compared with previous ELPI version (e.g., classic ELPI); b 50 percent cutting diameter; c Geometric mean diameter
40% 60% 12 95% 5% 20 95% 5% 26 5% 95% 36 Table S3. Key physicochemical properties of P25, TNTs, and TiO2/TNTs (). Material BET surface area (m2/g) Single total pore volume (cm3/g) Average pore diameter (nm) pHPZC P25 47 0.18 15.5 6.67 TNTs 272 1.26 18.6 2.56 TiO2/TNTs 187 0.85 17.8 2.93 Table S4. Parameters of first-order kinetic model for photo-degradation of BPA by different materials over 5 reuse cycles. Cycle Materials TiO2 TNTs TiO2/TNTs 1 k1 (min-1) 0.0849 0.0011 0.0470 R2 0.982 0.942 0.997 R (%) a 100 6.2 94.4 2 k1 (min-1) 0.0062 0.0009 0.0469 R2 0.965 0.962 0.997 R (%) 28.9 5.2 94.4 3 k1 (min-1) 0.0013 0.0005 0.0444 R2 0.957 0.995 0.996 R (%) 7.0 2.8 93.6 4 k1 (min-1) 0.0005 0.0008 0.0416 R2 0.965 0.929 0.997 R (%) 2.9 4.1 92.3 5 k1 (min-1) 0.0004 0.0003 0.0394 R2 0.812 0.993 0.996 R (%) 1.8 2.0 91.2 a Removal efficiency at 60 min;
Supplementary Table 1: Temporal variability of Pb isotope in Singapore aerosols. Data from Chen et al. (2016)a. Sampling period 206/207 6/7 2SE 208/206 8/6 2SE July 27-29, 2011 1.1415 0.0001 2.1192 0.0001 August 3-7, 2011 1.1508 0.0000 2.1086 0.0001 August 7-14, 2011 1.1489 0.0001 2.1122 0.0001 August 14-23, 2011 1.1496 0.0001 2.1110 0.0001 August 23-September 16, 2011 1.1488 0.0001 2.1121 0.0001 September 16-October 1, 2011 1.1481 0.0000 2.1117 0.0001 October 1-14, 2011 1.1462 0.0001 2.1133 0.0002 October 14-November 1, 2011 1.1467 0.0000 2.1116 0.0001 November 1-16, 2011 1.1478 0.0001 2.1116 0.0001 November 16-December 16, 2011 1.1467 0.0001 2.1122 0.0001 Dec 16, 2011-Jan 2, 2012 1.1539 0.0003 2.1075 0.0005 January 16-18, 2012 1.1480 0.0003 2.1105 0.0005 February 2-7, 2012 1.1496 0.0001 2.1118 0.0001 February 16-21, 2012 1.1507 0.0001 2.1079 0.0001 March 4-9, 2012 1.1474 0.0001 2.1104 0.0002 March 22-27, 2012 1.1491 0.0000 2.1103 0.0002 April 5-10, 2012 1.1469 0.0001 2.1112 0.0002 12-17, 2012 1.1486 0.0001 2.1109 0.0002 April 19- 24, 2012 1.1445 0.0000 2.1160 0.0001 April 26 - May 1, 2012 1.1433 0.0001 2.1169 0.0001
the control condition. N = number of studies; n = number of participants; d = Cohen’s d effect size; z = z score; p = exact p value. * p<.05, **p<.01, ***p<.001. Figure Three: Funnel plot of the post-intervention between-group effect sizes for psychosis symptom outcomes. Note: the trend line reflects the mean effect size.
Coastal 3.7 (3.5, 3.8) -0.72 0.51 13.97 (4.72, 23.17) South Wet Tropics Outershelf 15.9 (15.2, 16.7) -0.71 0.50 16.81 (5.49, 27.81) Midshelf 13.1 (12.2, 14.1) -0.65 0.42 21.43 (5.00, 38.29) Lagoon 12.3 (11.4, 13.3) -0.72 0.52 27.04 (10.31, 44.28) Inshore 7.2 (6.9, 7.6) -0.84 0.70 25.69 (15.05, 36.89) Coastal 3.6 (3.4, 3.8) -0.73 0.53 16.60 (6.03, 26.91) Burdekin Outershelf 15.6 (15.1, 16.1) 7.506E-06) -0.56 0.32 8.04 15.91) Midshelf 14.9 (14.2, 15.6) -0.59 0.35 12.55 (0.39, 23.65) Lagoon 13.9 (13.2, 14.5) -0.63 0.40 14.67 (2.07, 26.42) Inshore 8.5 (8.0, 9.1) -0.58 0.33 17.51 (-0.05, 33.27) Coastal 3.6 (3.4, 3.7) 4.950E-06) -0.55 0.30 11.95 (-0.86, 23.87)
“Supplementary Material” On the mechanism of molybdenite exfoliation during mechanical milling Hossein Shalchian,† Jalil Vahdati Khaki, †* Abolfazl Babakhani,† Giuliana Taglieri,‡ Ida De Michelis,‡ Valeria Daniele‡ and Francesco Veglio ‡ † Department of Materials Science and Metallurgical Engineering, Engineering Faculty, Ferdowsi University of Mashhad, Mashhad, Islamic Republic of Iran. ‡ Department of Industrial Engineering, Information and Economics, University of L’Aquila, Monteluco di Roio, 67100 L’Aquila, Italy Table S1. Milling conditions of each run for two groups of mechanical milling exfoliation Run number MoS2 (g) (g) B/P Milling time (hr) Run number MoS2 (g) Al2O3 (g) B/P Milling time (hr) 1 8 0 10 2 25 4 4 10 2 2 8 0 10 4 26 4 4 10 4
'Transaminases increased' Cholestatic Injury 'Mixed injury', 'Bilirubin conjugated increased', 'Bilirubin urine', 'Blood bilirubin abnormal', 'Blood bilirubin increased', 'Cholestasis', 'Hepatitis cholestatic', 'Hyperbilirubinaemia', 'Jaundice', 'Jaundice cholestatic', 'Urine bilirubin increased', 'Yellow skin' Hepatic failure ‘Coma hepatic', 'Hepatic encephalopathy',
Table S2. Incidence of Tp53 mutations in control rats from multiple NTP studies and TBBA-exposed rats, as reported in the final NTP study report (NTP, 2014b), and a publication using data from the same NTP study (Harvey et al., 2015). Treatment Group Final Report (NTP, 2014) Publication (Harvey et al., 2015) Controls 1/9 2/10 250 mg/kg 3/3 Not Provided 500 mg/kg 3/7 Not Provided 1000 mg/kg 4/6 Not Provided All Treated 10/16 15/22 p-value (control vs. all treated)1 < 0.05 Not Conducted Mutation type included in frequency count Only Functional Not Provided 1p-value (reported by NTP) generated with one-sided Fisher’s exact test Table S3. Statistical results comparing Tp53 mutation incidences between individual TBBPA dose groups. P-values are listed comparing the incidence of Tp53 mutation in each dose group against the control group, calculated in the current investigation as based off the one-sided Fisher Exact test. Statistics could not be fully carried out using data from the peer-reviewed publication, as data were not provided for individual treatment groups. Treatment Group Final Report (NTP, 2014) Publication (Harvey et al., 2015) 250 mg/kg 0.018 Data Not Provided 500 mg/kg 0.192 Data Not Provided 1000 mg/kg 0.047 Data Not Provided All Treated 0.017 0.015 500 mg/kg and 1000 mg/kg 0.052 Data Not Provided
Exponential4 13.76 5.34 0.07 0.07 0.76 1204.4 -0.12 0.06 Exponential5 13.76 2.34 0.07 0.07 0.76 1204.4 -0.12 0.06 Hill 12.37 2.52 0.07 0.07 0.86 1204.4 -0.08 0.02 Linear 11.61 8.88 0.07 0.07 0.34 1204.5 0.55 0.86 Polynomial 11.61 8.88 0.07 0.07 0.34 1204.5 0.55 0.86 Polynomial 11.61 8.88 0.07 0.07 0.34 1204.5 0.55 0.86 Power 11.61 8.88 0.07 0.07 0.34 1204.5 0.55 0.86 a Because the results of tests 2 and 3 indicated that the variance was not fit well (p<0.10), BMDs were also estimated using a modeled (non-constant) variance. Modeling the variance did not improve the fit of the variance model (Test 3 p = 0.03).
Table S1: Points of departure derived for monocrotalinea. Species Gender Tumour Type Malignant Dose(mg/kg bw/day) T25 (mg/kg bw/day) T10 (mg/kg bw/day) 0 2.5 Rat Male Pulmonary adenocarcinoma Yes 0/45b 10/60 3.8 1.5 Pulmonary adenocarcinoma with metastases Yes 0/45 1/60 38 15 Hepatocellular carcinoma Yes 0/45 5/60 7.5 3.0 Acute myelogenous leukemia Yes 0/45 3/60 13 5.2 Rhabdomyosarcoma Yes 0/45 4/60 9.4 3.8 Renal adenoma No 0/45 1/60 38 15 Peliosis hepatis No 0/45 8/60 4.7 1.9 Bile duct hyperplasia No 0/45 3/60 13 5.2 Adrenal adenoma No 2/45 8/60 6.7 2.7 a The data from Shumaker et al.(1976) b Italic number represents cancer incidence/total number of test animals
Table S4: Points of departure derived for symphytinea. Species Gender Tumour Type Malignant Dose(mg/kg bw/day) T25 (mg/kg bw/day) T10 (mg/kg bw/day) 0 6.26 Rat Male liver cell adenomas No 0/20b 1/20 31 12 Hemangioendothelial sarcoma of the liver Yes 0/20 3/20 10 4.0 Myeloid leukemia No 1/20 1/20 - Interstitial cell tumour of the testis No 1/20 0/20 - Fibroma of the back No 1/20 0/20 - a The data from Hirono et al.(1979) b Italic number represents cancer number of test animals
…Using approaches such as those described by the Adverse Outcome Pathway concept (Ankley et al. 2010) may help establish robust linkages between mechanistic endpoints and adverse effects. 3 IPCS MoA Framework This framework considers the following steps in the evaluation of potential MoAs. Problem formulation / Hypothesised MoA statement Summary of data for use in MoA analysis Listing of key events identified for a specific MoA Bradford Hill considerations for WoE of available data/information for MoA analysis in experimental species Dose response relationships and temporal association Consistency and specificity – biological plausibility Qualitative and quantitative human concordance 1a 1b 3
0.23 14.11 1.27 0.04 0.27 1.50 4.78 2.47 FBB12-162: Possible Japanese tephra (05/02/13) 1 0.01 12.18 0.72 0.06 0.01 0.51 3.82 4.71 92.58 2 0.34 11.05 2.12 0.06 0.43 2.42 3.56 2.21 94.61 3 0.60 12.65 3.12 0.13 0.76 3.52 3.97 0.78 97.98 4 0.35 11.08 2.23 0.07 0.41 2.54 3.67 2.23 95.42 5 0.02 14.52 0.59 0.06 0.06 0.62 4.69 4.38 98.79 6 0.60 12.90 3.42 0.13 0.74 3.20 4.50 0.81 7 0.28 14.62 1.59 0.02 0.23 2.82 3.99 2.05 99.92 8 0.28 12.01 2.17 0.06 0.47 2.32 3.51 2.23 98.33 9 0.34 11.41 2.07 0.04 0.40 2.19 3.30 2.35 97.45 0.03 11.68 0.76 0.06 0.00 0.39 3.29 4.52 96.27 0.31 11.91 2.14 0.04 0.43 2.13 3.58 2.30 98.69 JRB12-71: Mount St Helens (West set) (21/04/13) 1 0.20 12.84 1.52 0.03 0.23 1.42 4.61 2.38 96.41 2 0.18 13.20 1.47 0.03 0.24 1.37 4.29 2.54 96.68 3 0.16 12.00 1.51 0.03 0.19 1.47 4.04 2.35 95.54 4 0.23 12.42 1.34 0.03 0.14 0.87 4.22 2.65 95.98
Table S1 The IUPAC name, structure, Log P and molecular weight of the PIs PIs IUPAC name Log P Structure Darocure 1173; C10H12O2; Mw. 164.2 2-Hydroxy-2-methyl propiophenone 1.48 BP; C13H10O; Mw.182.2 Benzophenone 3.21 Darocure 184; C13H16O2; Mw.204.3 2.17 4-MBP; C14H12O; Mw.196.2 4-Methylbenzophenone 3.87 EDAB; C11H15NO2; Mw.193.2 2.48 OMBB; C15H12O3; Mw.240.2 Methyl 2-benzoylbenzoate 2.60 BDK; C16H16O3; Mw.256.3 3.62 2-ITX; C16H14SO; Mw.254.4 2-Isopropylthioxanthone 5.11 Irgacure 907; C15H21NO2S; Mw.279.4 2.44 DEAP; C12H16O3; Mw.208.2 2,2-Diethoxyacetophenone 2.39 PBZ; C19H14O; Mw.258.3 4-Benzoylbiphenyl 5.14 Irgacure 819; C26H27O3P; Mw.418.5 oxide 5.60 TPO; C22H21O2P; Mw.348.4 oxide 4.21
Variable % bias %reduct bias t p>t Region North U 37 4.7 0 . M 3.9 89.3 0.56 0.574 . Region West U -22.7 -2.94 0.003 . M 4.1 81.8 0.66 0.511 . Region East U 35.5 4.28 0 .
Total: Father = 3, Doctor = 2. CHAIN 13, F1 F1 ID: a49 RECALL Recent events in New Zealand started a debate about the risks of the diptherpox vaccine. A father of a little boy said that after he had the shot he fell ill with a fever and that doctors mentioned that his heart had swollen. Some of those that have had the vaccine have died as a result of its side effects. Scientists are under no doubt that the vaccine is very effective. 95% of the population has been vaccinated which makes an outbreak unlikely, but cases of the disease have been reported in areas with low uptake of the vaccine. A doctor commented that severe adverse effects of the vaccine were very rare and that the side effects are usually mild and temporary. FATHER A father of a little boy P2A = 1 said that after he had the shot P5A = 1 he fell ill with a fever P7A = 1 and that doctors mentioned that his heart had swollen. P8A = 1 Some of those that have had the vaccine have died as a result of its side effects. P9 = 1 DOCTOR Scientists are under no doubt that the vaccine is very effective. P1A = 1 P1B = 1 95% of the population has been vaccinated makes an outbreak unlikely, P4 A= 1 P4B = 1 but cases of the disease have been reported in areas with low uptake of the vaccine. P6 A=1
Generation (F3) : Condition (Condition 2) 1.53 1.45 Generation (F4) : Condition (Condition 2) -0.08 1.49 Generation * Age Model 5 88.27 (Intercept) -0.22 0.52 Generation (F2) -0.62 0.78 Generation (F3) 0.38 0.73 Generation (F4) -0.92 0.81 Z.Age 1.32 0.59 Generation + Condition * Generation 8 91.9 (Intercept) 0.51 0.73 Generation (F2) 0.59 1.1 Generation (F3) -1.02 1.03 Generation (F4) 0.59 1.1 Condition (Condition 2) -0.51 1.02 Generation (F2) : Condition (Condition 2) -0.08 1.49 Generation (F3) : Condition (Condition 2) 1.53 1.45 Generation (F4) : Condition (Condition 2) -0.08 1.49 Full model 10 73 (Intercept) -0.12 1.08 Generation (F2) 1.06 1.09 Generation (F3) -0.21 0.95 Generation (F4) 1.04 1.03 Nationality (British) 0.94 0.76 Gender (Male) -0.17 0.78 Condition (Condition 2) -0.38 0.75 Provaccination 2.87 0.86 Age -1.79 0.81 Ratio provaccination to total propositions -1.55 0.76
CH7 F1 CONDITION 2 (Father = provaccination, Doctor = antivaccination) RESPONSE: NO CONFIDENCE: 5 QUALITATIVE: would want to verify that extreme cases of the disease are rare and also look for opinions of other medical professionals. CH7 F2 CONDITION 2 (Father = provaccination, Doctor = antivaccination) RESPONSE: YES CONFIDENCE: 6 QUALITATIVE: Vaccination is a serious issue, we should be care full when citing a doctor because some of them have agendas to fulfil. The best thing would be to educate yourself on the science behind it. CH7 F3 CONDITION 2 (Father = provaccination, Doctor = antivaccination) RESPONSE: YES CONFIDENCE: 4 QUALITATIVE: - CH7 F4 CONDITION 2 (Father = provaccination, Doctor = antivaccination) RESPONSE: NO CONFIDENCE: 6 QUALITATIVE: - CH8 F1 CONDITION 2 (Father = provaccination, Doctor = antivaccination) RESPONSE: NO CONFIDENCE: 5 QUALITATIVE: At this point, I feel a little safer going with the opinion of the Doctor as he may not be as biased as a father when it involves his own children.
and reliably by the variables available in this study? 1.6. Did the authors control for any post-intervention variables that could have been affected by the intervention? No No No No No No 1.7. Did the authors use an appropriate analysis method that adjusted for all the important confounding domains and for time-varying confounding? No (e.g. compliance to treatment was not assessed) No (e.g. compliance to treatment was not assessed) No (e.g. no adjustment for concomitant medical conditions) No (e.g. general health problems may have contributed to the number of visits or concomitant treatments with drugs) No (e.g. no estimation of compliance to treatment, no correction of other confounders) Yes (patients were hospitalized and monitored for compliance, side effects and symptom change weekly) 1.8. If Y/PY to 1.7: Were confounding domains that were adjusted for measured validly and reliably by the variables available in this study? / / / / / / Risk of bias judgement Serious risk of bias Serious risk of bias Serious risk of bias Serious risk of bias Serious risk of bias Low risk of bias Bias in selection of participants into the study 2.1. Was selection of participants into the study (or into the analysis) based on participant characteristics observed after the start of intervention? No No No No No No 2.2. If Y/PY to 2.1: Were the post-intervention variables that influenced selection likely to be associated with intervention? / / / / / / 2.3 If Y/PY to 2.2: Were the post-intervention variables that influenced selection likely to be influenced by the outcome or a cause of the outcome? / / / / / / 2.4. Do start of follow-up and start of intervention coincide for most participants? Yes Yes No (change of intervention was based on clinician’s decision) Probably yes (it is not completely clear the congruence between prescriptions and PGx results) Probably yes (it is not completely clear the congruence between prescriptions and PGx results) No (the results of genotyping were available at week 4)
Supplementary 3: application of the GRACE checklist score (Dreyer et al., 2014) to estimate the quality of included observational studies. Study Scale item AmpliChip (Hodgson et al., 2014) AmpliChip (Hodgson et al., 2015) CNSDose (Bousman et al., 2017) GeneSight (Winner et al., 2013a) Genecept (Brennan et al., 2015) Genelex (Verbeurgt et al., 2014) HILOmet (Ruaño et al., 2013) Neuropharmagen (Espadaler et al., 2017) Pillcheck (Papastergiou et al., 2017) D1. Treatment details Yes Yes Yes No No No Yes No No D2. Suff. Details on primary outcomes Yes Yes Yes Yes Yes Yes Yes Yes Yes D3. Objective measure of primary Outcome Yes Yes Yes Yes Yes Yes Yes Yes Yes D4. Validated primary outcomes Yes Yes Yes Yes Yes Yes Yes Yes Yes D5. Primary outcome measured in the same way in all subjects Yes Yes Yes Yes Yes Yes Yes Yes Yes D6. Inclusion of important covariates Yes Yes No No No No Yes Yes No M1. Drug Naive or washout? No No Yes No No No No No No M2. Concurrent comparator groups? Yes Yes Yes Yes Yes Yes Yes Yes Yes M3. Were confounding factors considered? Yes Yes No No No No No No No M4. Free of Immortal time bias? No No No Yes No Yes Yes No Yes M5. Recursive analysis? No Yes No Yes Yes No No No No